updated version of textbook

01/1/.ipynb_checkpoints/ch1_intro-checkpoint.md

@@ -0,0 +1,39 @@
+# Introduction
+Data are descriptions of the world around us, collected through observation and
+stored on computers. Computers enable us to infer properties of the world from
+these descriptions. Data science is the discipline of drawing conclusions from
+data using computation. There are three core aspects of effective data
+analysis: exploration, prediction, and inference. This text develops a
+consistent approach to all three, introducing statistical ideas and fundamental
+ideas in computer science concurrently. We focus on a minimal set of core
+techniques that can be applied to a vast range of real-world
+applications. A foundation in data science requires not only understanding
+statistical and computational techniques, but also recognizing how they apply
+to real scenarios.
+
+For whatever aspect of the world we wish to study—whether it's the Earth's
+weather, the world's markets, political polls, or the human mind—data we
+collect typically offer an incomplete description of the subject at hand. A
+central challenge of data science is to make reliable conclusions using this
+partial information.
+
+In this endeavor, we will combine two essential tools: computation and
+randomization. For example, we may want to understand climate change trends
+using temperature observations. Computers will allow us to use all available
+information to draw conclusions. Rather than focusing only on the average
+temperature of a region, we will consider the whole range of temperatures
+together to construct a more nuanced analysis. Randomness will allow us to
+consider the many different ways in which incomplete information might be
+completed. Rather than assuming that temperatures vary in a particular way, we
+will learn to use randomness as a way to imagine many possible scenarios that
+are all consistent with the data we observe.
+
+Applying this approach requires learning to program a computer, and so this
+text interleaves a complete introduction to programming that assumes no prior
+knowledge. Readers with programming experience will find that we cover several
+topics in computation that do not appear in a typical introductory computer
+science curriculum. Data science also requires careful reasoning about numerical
+quantities, but this text does not assume any background in mathematics or
+statistics beyond basic algebra. You will find very few equations in this text.
+Instead, techniques are described to readers in the same language in which they
+are described to the computers that execute them — a programming language.

01/1/1/.ipynb_checkpoints/computational-tools-checkpoint.md

@@ -0,0 +1,24 @@
+<!-- #region -->
+# Computational Tools
+
+
+This text uses the Python 3 programming language, along with a standard set of
+numerical and data visualization tools that are used widely in commercial
+applications, scientific experiments, and open-source projects.
+Python has recruited enthusiasts from many professions that use data to draw
+conclusions. By learning the Python language, you will join a
+million-person-strong community of software developers and data scientists.
+
+A Python program can be executed by any computer, regardless of its
+manufacturer or operating system, provided that support for the language is
+installed. If you wish to install the version of Python and its accompanying
+libraries that will match this text, we recommend the [Anaconda][download]
+distribution that packages together the Python 3 language interpreter, IPython
+libraries, and the Jupyter notebook environment.
+
+   [download]: http://continuum.io/downloads
+
+This text includes a complete introduction to all of these computational tools.
+You will learn to write programs, generate images from data, and work with
+real-world data sets that are published online.
+<!-- #endregion -->

01/1/1/computational-tools.md

@@ -0,0 +1,24 @@
+<!-- #region -->
+# Computational Tools
+
+
+This text uses the Python 3 programming language, along with a standard set of
+numerical and data visualization tools that are used widely in commercial
+applications, scientific experiments, and open-source projects.
+Python has recruited enthusiasts from many professions that use data to draw
+conclusions. By learning the Python language, you will join a
+million-person-strong community of software developers and data scientists.
+
+A Python program can be executed by any computer, regardless of its
+manufacturer or operating system, provided that support for the language is
+installed. If you wish to install the version of Python and its accompanying
+libraries that will match this text, we recommend the [Anaconda][download]
+distribution that packages together the Python 3 language interpreter, IPython
+libraries, and the Jupyter notebook environment.
+
+   [download]: http://continuum.io/downloads
+
+This text includes a complete introduction to all of these computational tools.
+You will learn to write programs, generate images from data, and work with
+real-world data sets that are published online.
+<!-- #endregion -->

01/1/2/.ipynb_checkpoints/statistical-techniques-checkpoint.md

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+# Statistical Techniques
+The discipline of statistics has long addressed the same fundamental challenge
+as data science: how to draw robust conclusions about the world using incomplete
+information. One of the most important contributions of statistics is a
+consistent and precise vocabulary for describing the relationship between
+observations and conclusions. This text continues in the same tradition,
+focusing on a set of core inferential problems from statistics: testing
+hypotheses, estimating confidence, and predicting unknown quantities.
+
+Data science extends the field of statistics by taking full advantage of
+computing, data visualization, machine learning, optimization, and access 
+to information. The combination of fast computers and the Internet gives 
+anyone the ability to access and analyze
+vast datasets: millions of news articles, full encyclopedias, databases for
+any domain, and massive repositories of music, photos, and video.
+
+Applications to real data sets motivate the statistical techniques that we
+describe throughout the text. Real data often do not follow regular patterns or
+match standard equations. The interesting variation in real data can be lost by
+focusing too much attention on simplistic summaries such as average values.
+Computers enable a family of methods based on resampling that apply to a wide
+range of different inference problems, take into account all available
+information, and require few assumptions or conditions. Although these
+techniques have often been reserved for advanced courses in statistics, their
+flexibility and simplicity are a natural fit for data science applications.
+

01/1/2/statistical-techniques.md

@@ -0,0 +1,26 @@
+# Statistical Techniques
+The discipline of statistics has long addressed the same fundamental challenge
+as data science: how to draw robust conclusions about the world using incomplete
+information. One of the most important contributions of statistics is a
+consistent and precise vocabulary for describing the relationship between
+observations and conclusions. This text continues in the same tradition,
+focusing on a set of core inferential problems from statistics: testing
+hypotheses, estimating confidence, and predicting unknown quantities.
+
+Data science extends the field of statistics by taking full advantage of
+computing, data visualization, machine learning, optimization, and access 
+to information. The combination of fast computers and the Internet gives 
+anyone the ability to access and analyze
+vast datasets: millions of news articles, full encyclopedias, databases for
+any domain, and massive repositories of music, photos, and video.
+
+Applications to real data sets motivate the statistical techniques that we
+describe throughout the text. Real data often do not follow regular patterns or
+match standard equations. The interesting variation in real data can be lost by
+focusing too much attention on simplistic summaries such as average values.
+Computers enable a family of methods based on resampling that apply to a wide
+range of different inference problems, take into account all available
+information, and require few assumptions or conditions. Although these
+techniques have often been reserved for advanced courses in statistics, their
+flexibility and simplicity are a natural fit for data science applications.
+

01/1/ch1_intro.md

@@ -0,0 +1,39 @@
+# Introduction
+Data are descriptions of the world around us, collected through observation and
+stored on computers. Computers enable us to infer properties of the world from
+these descriptions. Data science is the discipline of drawing conclusions from
+data using computation. There are three core aspects of effective data
+analysis: exploration, prediction, and inference. This text develops a
+consistent approach to all three, introducing statistical ideas and fundamental
+ideas in computer science concurrently. We focus on a minimal set of core
+techniques that can be applied to a vast range of real-world
+applications. A foundation in data science requires not only understanding
+statistical and computational techniques, but also recognizing how they apply
+to real scenarios.
+
+For whatever aspect of the world we wish to study—whether it's the Earth's
+weather, the world's markets, political polls, or the human mind—data we
+collect typically offer an incomplete description of the subject at hand. A
+central challenge of data science is to make reliable conclusions using this
+partial information.
+
+In this endeavor, we will combine two essential tools: computation and
+randomization. For example, we may want to understand climate change trends
+using temperature observations. Computers will allow us to use all available
+information to draw conclusions. Rather than focusing only on the average
+temperature of a region, we will consider the whole range of temperatures
+together to construct a more nuanced analysis. Randomness will allow us to
+consider the many different ways in which incomplete information might be
+completed. Rather than assuming that temperatures vary in a particular way, we
+will learn to use randomness as a way to imagine many possible scenarios that
+are all consistent with the data we observe.
+
+Applying this approach requires learning to program a computer, and so this
+text interleaves a complete introduction to programming that assumes no prior
+knowledge. Readers with programming experience will find that we cover several
+topics in computation that do not appear in a typical introductory computer
+science curriculum. Data science also requires careful reasoning about numerical
+quantities, but this text does not assume any background in mathematics or
+statistics beyond basic algebra. You will find very few equations in this text.
+Instead, techniques are described to readers in the same language in which they
+are described to the computers that execute them — a programming language.

01/2/.ipynb_checkpoints/why-data-science-checkpoint.md

@@ -0,0 +1,27 @@
+# Why Data Science?
+Most important decisions are made with only partial information and uncertain
+outcomes. However, the degree of uncertainty for many decisions can be reduced
+sharply by access to large data sets and the computational tools
+required to analyze them effectively. Data-driven decision making has already
+transformed a tremendous breadth of industries, including finance, advertising,
+manufacturing, and real estate. At the same time, a wide range of academic
+disciplines are evolving rapidly to incorporate large-scale data analysis into
+their theory and practice.
+
+Studying data science enables individuals to bring these techniques to bear on
+their work, their scientific endeavors, and their personal decisions. Critical
+thinking has long been a hallmark of a rigorous education, but critiques are
+often most effective when supported by data. A critical analysis of any aspect
+of the world, may it be business or social science, involves inductive
+reasoning; conclusions can rarely been proven outright, but only supported by
+the available evidence. Data science provides the means to make precise,
+reliable, and quantitative arguments about any set of observations. With
+unprecedented access to information and computing, critical thinking about
+any aspect of the world that can be measured would be incomplete without
+effective inferential techniques.
+
+The world has too many unanswered questions and difficult challenges to leave
+this critical reasoning to only a few specialists. All educated members of 
+society can build the capacity to reason about data. The tools, techniques, 
+and data sets are all readily available; this text aims to make them 
+accessible to everyone.

01/2/why-data-science.md

@@ -0,0 +1,27 @@
+# Why Data Science?
+Most important decisions are made with only partial information and uncertain
+outcomes. However, the degree of uncertainty for many decisions can be reduced
+sharply by access to large data sets and the computational tools
+required to analyze them effectively. Data-driven decision making has already
+transformed a tremendous breadth of industries, including finance, advertising,
+manufacturing, and real estate. At the same time, a wide range of academic
+disciplines are evolving rapidly to incorporate large-scale data analysis into
+their theory and practice.
+
+Studying data science enables individuals to bring these techniques to bear on
+their work, their scientific endeavors, and their personal decisions. Critical
+thinking has long been a hallmark of a rigorous education, but critiques are
+often most effective when supported by data. A critical analysis of any aspect
+of the world, may it be business or social science, involves inductive
+reasoning; conclusions can rarely been proven outright, but only supported by
+the available evidence. Data science provides the means to make precise,
+reliable, and quantitative arguments about any set of observations. With
+unprecedented access to information and computing, critical thinking about
+any aspect of the world that can be measured would be incomplete without
+effective inferential techniques.
+
+The world has too many unanswered questions and difficult challenges to leave
+this critical reasoning to only a few specialists. All educated members of 
+society can build the capacity to reason about data. The tools, techniques, 
+and data sets are all readily available; this text aims to make them 
+accessible to everyone.

01/3/.ipynb_checkpoints/Plotting_the_Classics-checkpoint.ipynb

@@ -0,0 +1,360 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "from urllib.request import urlopen \n",
+    "import re\n",
+    "def read_url(url): \n",
+    "    return re.sub('\\\\s+', ' ', urlopen(url).read().decode())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Plotting the classics\n",
+    "In this example, we will explore statistics for two classic novels: *The Adventures of Huckleberry Finn* by Mark Twain, and *Little Women* by Louisa May Alcott. The text of any book can be read by a computer at great speed. Books published before 1923 are currently in the *public domain*, meaning that everyone has the right to copy or use the text in any way. [Project Gutenberg](http://www.gutenberg.org/) is a website that publishes public domain books online. Using Python, we can load the text of these books directly from the web.\n",
+    "\n",
+    "This example is meant to illustrate some of the broad themes of this text. Don't worry if the details of the program don't yet make sense. Instead, focus on interpreting the images generated below. Later sections of the text will describe most of the features of the Python programming language used below.\n",
+    "\n",
+    "First, we read the text of both books into lists of chapters, called `huck_finn_chapters` and `little_women_chapters`. In Python, a name cannot contain any spaces, and so we will often use an underscore `_` to stand in for a space. The `=` in the lines below give a name on the left to the result of some computation described on the right. A *uniform resource locator* or *URL* is an address on the Internet for some content; in this case, the text of a book. The `#` symbol starts a comment, which is ignored by the computer but helpful for people reading the code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read two books, fast!\n",
+    "\n",
+    "huck_finn_url = 'https://www.inferentialthinking.com/data/huck_finn.txt'\n",
+    "huck_finn_text = read_url(huck_finn_url)\n",
+    "huck_finn_chapters = huck_finn_text.split('CHAPTER ')[44:]\n",
+    "\n",
+    "little_women_url = 'https://www.inferentialthinking.com/data/little_women.txt'\n",
+    "little_women_text = read_url(little_women_url)\n",
+    "little_women_chapters = little_women_text.split('CHAPTER ')[1:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "While a computer cannot understand the text of a book, it can provide us with some insight into the structure of the text. The name `huck_finn_chapters` is currently bound to a list of all the chapters in the book. We can place them into a table to see how each chapter begins."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Chapters</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>I. YOU don't know about me without you have re...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>II. WE went tiptoeing along a path amongst the...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>III. WELL, I got a good going-over in the morn...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>IV. WELL, three or four months run along, and ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>V. I had shut the door to. Then I turned aroun...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>VI. WELL, pretty soon the old man was up and a...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>VII. \"GIT up! What you 'bout?\" I opened my eye...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>VIII. THE sun was up so high when I waked that...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>IX. I wanted to go and look at a place right a...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>X. AFTER breakfast I wanted to talk about the ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>XI. \"COME in,\" says the woman, and I did. She ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>XII. IT must a been close on to one o'clock wh...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>XIII. WELL, I catched my breath and most faint...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>XIV. BY and by, when we got up, we turned over...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>XV. WE judged that three nights more would fet...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>XVI. WE slept most all day, and started out at...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>XVII. IN about a minute somebody spoke out of ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>XVIII. COL. Grangerford was a gentleman, you s...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>XIX. TWO or three days and nights went by; I r...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>XX. THEY asked us considerable many questions;...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>XXI. IT was after sun-up now, but we went righ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>XXII. THEY swarmed up towards Sherburn's house...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>XXIII. WELL, all day him and the king was hard...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>XXIV. NEXT day, towards night, we laid up unde...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>XXV. THE news was all over town in two minutes...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>XXVI. WELL, when they was all gone the king he...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>XXVII. I crept to their doors and listened; th...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>XXVIII. BY and by it was getting-up time. So I...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>XXIX. THEY was fetching a very nice-looking ol...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>XXX. WHEN they got aboard the king went for me...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>XXXI. WE dasn't stop again at any town for day...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>XXXII. WHEN I got there it was all still and S...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>XXXIII. SO I started for town in the wagon, an...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>XXXIV. WE stopped talking, and got to thinking...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>XXXV. IT would be most an hour yet till breakf...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>XXXVI. AS soon as we reckoned everybody was as...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>XXXVII. THAT was all fixed. So then we went aw...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>XXXVIII. MAKING them pens was a distressid tou...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>XXXIX. IN the morning we went up to the villag...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>XL. WE was feeling pretty good after breakfast...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>XLI. THE doctor was an old man; a very nice, k...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>XLII. THE old man was uptown again before brea...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>THE LAST THE first time I catched Tom private ...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                             Chapters\n",
+       "0   I. YOU don't know about me without you have re...\n",
+       "1   II. WE went tiptoeing along a path amongst the...\n",
+       "2   III. WELL, I got a good going-over in the morn...\n",
+       "3   IV. WELL, three or four months run along, and ...\n",
+       "4   V. I had shut the door to. Then I turned aroun...\n",
+       "5   VI. WELL, pretty soon the old man was up and a...\n",
+       "6   VII. \"GIT up! What you 'bout?\" I opened my eye...\n",
+       "7   VIII. THE sun was up so high when I waked that...\n",
+       "8   IX. I wanted to go and look at a place right a...\n",
+       "9   X. AFTER breakfast I wanted to talk about the ...\n",
+       "10  XI. \"COME in,\" says the woman, and I did. She ...\n",
+       "11  XII. IT must a been close on to one o'clock wh...\n",
+       "12  XIII. WELL, I catched my breath and most faint...\n",
+       "13  XIV. BY and by, when we got up, we turned over...\n",
+       "14  XV. WE judged that three nights more would fet...\n",
+       "15  XVI. WE slept most all day, and started out at...\n",
+       "16  XVII. IN about a minute somebody spoke out of ...\n",
+       "17  XVIII. COL. Grangerford was a gentleman, you s...\n",
+       "18  XIX. TWO or three days and nights went by; I r...\n",
+       "19  XX. THEY asked us considerable many questions;...\n",
+       "20  XXI. IT was after sun-up now, but we went righ...\n",
+       "21  XXII. THEY swarmed up towards Sherburn's house...\n",
+       "22  XXIII. WELL, all day him and the king was hard...\n",
+       "23  XXIV. NEXT day, towards night, we laid up unde...\n",
+       "24  XXV. THE news was all over town in two minutes...\n",
+       "25  XXVI. WELL, when they was all gone the king he...\n",
+       "26  XXVII. I crept to their doors and listened; th...\n",
+       "27  XXVIII. BY and by it was getting-up time. So I...\n",
+       "28  XXIX. THEY was fetching a very nice-looking ol...\n",
+       "29  XXX. WHEN they got aboard the king went for me...\n",
+       "30  XXXI. WE dasn't stop again at any town for day...\n",
+       "31  XXXII. WHEN I got there it was all still and S...\n",
+       "32  XXXIII. SO I started for town in the wagon, an...\n",
+       "33  XXXIV. WE stopped talking, and got to thinking...\n",
+       "34  XXXV. IT would be most an hour yet till breakf...\n",
+       "35  XXXVI. AS soon as we reckoned everybody was as...\n",
+       "36  XXXVII. THAT was all fixed. So then we went aw...\n",
+       "37  XXXVIII. MAKING them pens was a distressid tou...\n",
+       "38  XXXIX. IN the morning we went up to the villag...\n",
+       "39  XL. WE was feeling pretty good after breakfast...\n",
+       "40  XLI. THE doctor was an old man; a very nice, k...\n",
+       "41  XLII. THE old man was uptown again before brea...\n",
+       "42  THE LAST THE first time I catched Tom private ..."
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Display the chapters of Huckleberry Finn in a dataframe.\n",
+    "\n",
+    "pd.DataFrame({'Chapters':huck_finn_chapters})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each chapter begins with a chapter number in Roman numerals, followed by the first sentence of the chapter. Project Gutenberg has printed the first word of each chapter in upper case. "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

01/3/Plotting_the_Classics.ipynb

@@ -0,0 +1,360 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')\n",
+    "\n",
+    "from urllib.request import urlopen \n",
+    "import re\n",
+    "def read_url(url): \n",
+    "    return re.sub('\\\\s+', ' ', urlopen(url).read().decode())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Plotting the classics\n",
+    "In this example, we will explore statistics for two classic novels: *The Adventures of Huckleberry Finn* by Mark Twain, and *Little Women* by Louisa May Alcott. The text of any book can be read by a computer at great speed. Books published before 1923 are currently in the *public domain*, meaning that everyone has the right to copy or use the text in any way. [Project Gutenberg](http://www.gutenberg.org/) is a website that publishes public domain books online. Using Python, we can load the text of these books directly from the web.\n",
+    "\n",
+    "This example is meant to illustrate some of the broad themes of this text. Don't worry if the details of the program don't yet make sense. Instead, focus on interpreting the images generated below. Later sections of the text will describe most of the features of the Python programming language used below.\n",
+    "\n",
+    "First, we read the text of both books into lists of chapters, called `huck_finn_chapters` and `little_women_chapters`. In Python, a name cannot contain any spaces, and so we will often use an underscore `_` to stand in for a space. The `=` in the lines below give a name on the left to the result of some computation described on the right. A *uniform resource locator* or *URL* is an address on the Internet for some content; in this case, the text of a book. The `#` symbol starts a comment, which is ignored by the computer but helpful for people reading the code."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Read two books, fast!\n",
+    "\n",
+    "huck_finn_url = 'https://www.inferentialthinking.com/data/huck_finn.txt'\n",
+    "huck_finn_text = read_url(huck_finn_url)\n",
+    "huck_finn_chapters = huck_finn_text.split('CHAPTER ')[44:]\n",
+    "\n",
+    "little_women_url = 'https://www.inferentialthinking.com/data/little_women.txt'\n",
+    "little_women_text = read_url(little_women_url)\n",
+    "little_women_chapters = little_women_text.split('CHAPTER ')[1:]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "While a computer cannot understand the text of a book, it can provide us with some insight into the structure of the text. The name `huck_finn_chapters` is currently bound to a list of all the chapters in the book. We can place them into a table to see how each chapter begins."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Chapters</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>I. YOU don't know about me without you have re...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>II. WE went tiptoeing along a path amongst the...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>III. WELL, I got a good going-over in the morn...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>IV. WELL, three or four months run along, and ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>V. I had shut the door to. Then I turned aroun...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>VI. WELL, pretty soon the old man was up and a...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>VII. \"GIT up! What you 'bout?\" I opened my eye...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>VIII. THE sun was up so high when I waked that...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>IX. I wanted to go and look at a place right a...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>X. AFTER breakfast I wanted to talk about the ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>XI. \"COME in,\" says the woman, and I did. She ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>XII. IT must a been close on to one o'clock wh...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>XIII. WELL, I catched my breath and most faint...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>XIV. BY and by, when we got up, we turned over...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>XV. WE judged that three nights more would fet...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>XVI. WE slept most all day, and started out at...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>XVII. IN about a minute somebody spoke out of ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>XVIII. COL. Grangerford was a gentleman, you s...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>XIX. TWO or three days and nights went by; I r...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>XX. THEY asked us considerable many questions;...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>XXI. IT was after sun-up now, but we went righ...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>XXII. THEY swarmed up towards Sherburn's house...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>XXIII. WELL, all day him and the king was hard...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>23</th>\n",
+       "      <td>XXIV. NEXT day, towards night, we laid up unde...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>24</th>\n",
+       "      <td>XXV. THE news was all over town in two minutes...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25</th>\n",
+       "      <td>XXVI. WELL, when they was all gone the king he...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26</th>\n",
+       "      <td>XXVII. I crept to their doors and listened; th...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>27</th>\n",
+       "      <td>XXVIII. BY and by it was getting-up time. So I...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>28</th>\n",
+       "      <td>XXIX. THEY was fetching a very nice-looking ol...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>XXX. WHEN they got aboard the king went for me...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>30</th>\n",
+       "      <td>XXXI. WE dasn't stop again at any town for day...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>31</th>\n",
+       "      <td>XXXII. WHEN I got there it was all still and S...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>32</th>\n",
+       "      <td>XXXIII. SO I started for town in the wagon, an...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>33</th>\n",
+       "      <td>XXXIV. WE stopped talking, and got to thinking...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>34</th>\n",
+       "      <td>XXXV. IT would be most an hour yet till breakf...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>35</th>\n",
+       "      <td>XXXVI. AS soon as we reckoned everybody was as...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>36</th>\n",
+       "      <td>XXXVII. THAT was all fixed. So then we went aw...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>37</th>\n",
+       "      <td>XXXVIII. MAKING them pens was a distressid tou...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>38</th>\n",
+       "      <td>XXXIX. IN the morning we went up to the villag...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>39</th>\n",
+       "      <td>XL. WE was feeling pretty good after breakfast...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>40</th>\n",
+       "      <td>XLI. THE doctor was an old man; a very nice, k...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>41</th>\n",
+       "      <td>XLII. THE old man was uptown again before brea...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>42</th>\n",
+       "      <td>THE LAST THE first time I catched Tom private ...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                             Chapters\n",
+       "0   I. YOU don't know about me without you have re...\n",
+       "1   II. WE went tiptoeing along a path amongst the...\n",
+       "2   III. WELL, I got a good going-over in the morn...\n",
+       "3   IV. WELL, three or four months run along, and ...\n",
+       "4   V. I had shut the door to. Then I turned aroun...\n",
+       "5   VI. WELL, pretty soon the old man was up and a...\n",
+       "6   VII. \"GIT up! What you 'bout?\" I opened my eye...\n",
+       "7   VIII. THE sun was up so high when I waked that...\n",
+       "8   IX. I wanted to go and look at a place right a...\n",
+       "9   X. AFTER breakfast I wanted to talk about the ...\n",
+       "10  XI. \"COME in,\" says the woman, and I did. She ...\n",
+       "11  XII. IT must a been close on to one o'clock wh...\n",
+       "12  XIII. WELL, I catched my breath and most faint...\n",
+       "13  XIV. BY and by, when we got up, we turned over...\n",
+       "14  XV. WE judged that three nights more would fet...\n",
+       "15  XVI. WE slept most all day, and started out at...\n",
+       "16  XVII. IN about a minute somebody spoke out of ...\n",
+       "17  XVIII. COL. Grangerford was a gentleman, you s...\n",
+       "18  XIX. TWO or three days and nights went by; I r...\n",
+       "19  XX. THEY asked us considerable many questions;...\n",
+       "20  XXI. IT was after sun-up now, but we went righ...\n",
+       "21  XXII. THEY swarmed up towards Sherburn's house...\n",
+       "22  XXIII. WELL, all day him and the king was hard...\n",
+       "23  XXIV. NEXT day, towards night, we laid up unde...\n",
+       "24  XXV. THE news was all over town in two minutes...\n",
+       "25  XXVI. WELL, when they was all gone the king he...\n",
+       "26  XXVII. I crept to their doors and listened; th...\n",
+       "27  XXVIII. BY and by it was getting-up time. So I...\n",
+       "28  XXIX. THEY was fetching a very nice-looking ol...\n",
+       "29  XXX. WHEN they got aboard the king went for me...\n",
+       "30  XXXI. WE dasn't stop again at any town for day...\n",
+       "31  XXXII. WHEN I got there it was all still and S...\n",
+       "32  XXXIII. SO I started for town in the wagon, an...\n",
+       "33  XXXIV. WE stopped talking, and got to thinking...\n",
+       "34  XXXV. IT would be most an hour yet till breakf...\n",
+       "35  XXXVI. AS soon as we reckoned everybody was as...\n",
+       "36  XXXVII. THAT was all fixed. So then we went aw...\n",
+       "37  XXXVIII. MAKING them pens was a distressid tou...\n",
+       "38  XXXIX. IN the morning we went up to the villag...\n",
+       "39  XL. WE was feeling pretty good after breakfast...\n",
+       "40  XLI. THE doctor was an old man; a very nice, k...\n",
+       "41  XLII. THE old man was uptown again before brea...\n",
+       "42  THE LAST THE first time I catched Tom private ..."
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Display the chapters of Huckleberry Finn in a dataframe.\n",
+    "\n",
+    "pd.DataFrame({'Chapters':huck_finn_chapters})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each chapter begins with a chapter number in Roman numerals, followed by the first sentence of the chapter. Project Gutenberg has printed the first word of each chapter in upper case. "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

01/what-is-data-science.md

@@ -0,0 +1,19 @@
+# 1. What is Data Science?
+Data Science is about drawing useful conclusions from large and diverse data
+sets through exploration, prediction, and inference.  Exploration involves
+identifying patterns in information.  Prediction involves using information
+we know to make informed guesses about values we wish we knew.  Inference
+involves quantifying our degree of certainty: will the patterns that we found in our data also appear in new observations? How accurate are our predictions? Our primary
+tools for exploration are visualizations and descriptive statistics, for
+prediction are machine learning and optimization, and for inference are
+statistical tests and models.
+
+Statistics is a central component of data science because statistics
+studies how to make robust conclusions based on incomplete information. Computing
+is a central component because programming allows us to apply analysis
+techniques to the large and diverse data sets that arise in real-world
+applications: not just numbers, but text, images, videos, and sensor readings.
+Data science is all of these things, but it is more than the sum of its parts
+because of the applications. Through understanding a particular domain, data
+scientists learn to ask appropriate questions about their data and correctly
+interpret the answers provided by our inferential and computational tools.

02/1/.ipynb_checkpoints/observation-and-visualization-john-snow-and-the-broad-street-pump-checkpoint.md

@@ -0,0 +1,93 @@
+# Observation and Visualization: John Snow and the Broad Street Pump
+One of the most powerful examples of astute observation eventually leading to the
+establishment of causality dates back more than 150 years. To get your mind into
+the right timeframe, try to imagine London in the 1850’s. It was the world’s
+wealthiest city but many of its people were desperately poor. Charles Dickens,
+then at the height of his fame, was writing about their plight. Disease was rife
+in the poorer parts of the city, and cholera was among the most feared. It was
+not yet known that germs cause disease; the leading theory was that “miasmas”
+were the main culprit. Miasmas manifested themselves as bad smells, and were
+thought to be invisible poisonous particles arising out of decaying matter.
+Parts of London did smell very bad, especially in hot weather. To protect
+themselves against infection, those who could afford to held sweet-smelling
+things to their noses.
+
+For several years, a doctor by the name of John Snow had been following the
+devastating waves of cholera that hit England from time to time. The disease
+arrived suddenly and was almost immediately deadly: people died within a day or
+two of contracting it, hundreds could die in a week, and the total death toll in
+a single wave could reach tens of thousands. Snow was skeptical of the miasma
+theory. He had noticed that while entire households were wiped out by cholera,
+the people in neighboring houses sometimes remained completely unaffected. As
+they were breathing the same air—and miasmas—as their neighbors, there was no
+compelling association between bad smells and the incidence of cholera.
+
+Snow had also noticed that the onset of the disease almost always involved
+vomiting and diarrhea. He therefore believed that the infection was carried by
+something people ate or drank, not by the air that they breathed. His prime
+suspect was water contaminated by sewage.
+
+At the end of August 1854, cholera struck in the overcrowded Soho district of
+London. As the deaths mounted, Snow recorded them diligently, using a method
+that went on to become standard in the study of how diseases spread: *he drew a
+map*. On a street map of the district, he recorded the location of each death.
+
+Here is Snow’s original map. Each black bar represents one death. When there are multiple deaths at the same address, the bars corresponding to those deaths are stacked on top of each other. The black
+discs mark the locations of water pumps. The map displays a striking
+revelation—the deaths are roughly clustered around the Broad Street pump.
+![Snow’s Cholera Map](../../images/snow_map.jpg)
+
+Snow studied his map carefully and investigated the apparent anomalies. All of
+them implicated the Broad Street pump. For example:
+- There were deaths in houses that were nearer the Rupert Street pump than the
+  Broad Street pump. Though the Rupert Street pump was closer as the crow flies,
+  it was less convenient to get to because of dead ends and the layout of the
+  streets. The residents in those houses used the Broad Street pump instead.
+- There were no deaths in two blocks just east of the pump. That was the
+  location of the Lion Brewery, where the workers drank what they brewed. If
+  they wanted water, the brewery had its own well.
+- There were scattered deaths in houses several blocks away from the Broad
+  Street pump. Those were children who drank from the Broad Street pump on their
+  way to school. The pump’s water was known to be cool and refreshing.
+
+The final piece of evidence in support of Snow’s theory was provided by two
+isolated deaths in the leafy and genteel Hampstead area, quite far from Soho.
+Snow was puzzled by these until he learned that the deceased were Mrs. Susannah
+Eley, who had once lived in Broad Street, and her niece. Mrs. Eley had water
+from the Broad Street pump delivered to her in Hampstead every day. She liked
+its taste.
+
+Later it was discovered that a cesspit that was just a few feet away from the
+well of the Broad Street pump had been leaking into the well. Thus the pump’s
+water was contaminated by sewage from the houses of cholera victims.
+
+Snow used his map to convince local authorities to remove the handle of the
+Broad Street pump. Though the cholera epidemic was already on the wane when he
+did so, it is possible that the disabling of the pump prevented many deaths from
+future waves of the disease.
+
+The removal of the Broad Street pump handle has become the stuff of legend. At
+the Centers for Disease Control (CDC) in Atlanta, when scientists look for
+simple answers to questions about epidemics, they sometimes ask each other,
+“Where is the handle to this pump?”
+
+Snow’s map is one of the earliest and most powerful uses of data visualization.
+Disease maps of various kinds are now a standard tool for tracking epidemics.
+
+**Towards Causality**
+
+Though the map gave Snow a strong indication that  the cleanliness of the water
+supply was the key to controlling cholera, he was still a long way from a
+convincing scientific argument that contaminated water was causing the spread of
+the disease. To make a more compelling case, he had to use the method of
+*comparison*.
+
+Scientists use comparison to identify an association between a treatment and an
+outcome. They compare the outcomes of a group of individuals who got the
+treatment (the *treatment group*) to the outcomes of a group who did not (the
+*control group*). For example, researchers today might compare the average
+murder rate in states that have the death penalty with the average murder rate
+in states that don’t.
+
+If the results are different, that is evidence for an association. To determine
+causation, however, even more care is needed.

02/1/observation-and-visualization-john-snow-and-the-broad-street-pump.md

@@ -0,0 +1,93 @@
+# Observation and Visualization: John Snow and the Broad Street Pump
+One of the most powerful examples of astute observation eventually leading to the
+establishment of causality dates back more than 150 years. To get your mind into
+the right timeframe, try to imagine London in the 1850’s. It was the world’s
+wealthiest city but many of its people were desperately poor. Charles Dickens,
+then at the height of his fame, was writing about their plight. Disease was rife
+in the poorer parts of the city, and cholera was among the most feared. It was
+not yet known that germs cause disease; the leading theory was that “miasmas”
+were the main culprit. Miasmas manifested themselves as bad smells, and were
+thought to be invisible poisonous particles arising out of decaying matter.
+Parts of London did smell very bad, especially in hot weather. To protect
+themselves against infection, those who could afford to held sweet-smelling
+things to their noses.
+
+For several years, a doctor by the name of John Snow had been following the
+devastating waves of cholera that hit England from time to time. The disease
+arrived suddenly and was almost immediately deadly: people died within a day or
+two of contracting it, hundreds could die in a week, and the total death toll in
+a single wave could reach tens of thousands. Snow was skeptical of the miasma
+theory. He had noticed that while entire households were wiped out by cholera,
+the people in neighboring houses sometimes remained completely unaffected. As
+they were breathing the same air—and miasmas—as their neighbors, there was no
+compelling association between bad smells and the incidence of cholera.
+
+Snow had also noticed that the onset of the disease almost always involved
+vomiting and diarrhea. He therefore believed that the infection was carried by
+something people ate or drank, not by the air that they breathed. His prime
+suspect was water contaminated by sewage.
+
+At the end of August 1854, cholera struck in the overcrowded Soho district of
+London. As the deaths mounted, Snow recorded them diligently, using a method
+that went on to become standard in the study of how diseases spread: *he drew a
+map*. On a street map of the district, he recorded the location of each death.
+
+Here is Snow’s original map. Each black bar represents one death. When there are multiple deaths at the same address, the bars corresponding to those deaths are stacked on top of each other. The black
+discs mark the locations of water pumps. The map displays a striking
+revelation—the deaths are roughly clustered around the Broad Street pump.
+![Snow’s Cholera Map](../../images/snow_map.jpg)
+
+Snow studied his map carefully and investigated the apparent anomalies. All of
+them implicated the Broad Street pump. For example:
+- There were deaths in houses that were nearer the Rupert Street pump than the
+  Broad Street pump. Though the Rupert Street pump was closer as the crow flies,
+  it was less convenient to get to because of dead ends and the layout of the
+  streets. The residents in those houses used the Broad Street pump instead.
+- There were no deaths in two blocks just east of the pump. That was the
+  location of the Lion Brewery, where the workers drank what they brewed. If
+  they wanted water, the brewery had its own well.
+- There were scattered deaths in houses several blocks away from the Broad
+  Street pump. Those were children who drank from the Broad Street pump on their
+  way to school. The pump’s water was known to be cool and refreshing.
+
+The final piece of evidence in support of Snow’s theory was provided by two
+isolated deaths in the leafy and genteel Hampstead area, quite far from Soho.
+Snow was puzzled by these until he learned that the deceased were Mrs. Susannah
+Eley, who had once lived in Broad Street, and her niece. Mrs. Eley had water
+from the Broad Street pump delivered to her in Hampstead every day. She liked
+its taste.
+
+Later it was discovered that a cesspit that was just a few feet away from the
+well of the Broad Street pump had been leaking into the well. Thus the pump’s
+water was contaminated by sewage from the houses of cholera victims.
+
+Snow used his map to convince local authorities to remove the handle of the
+Broad Street pump. Though the cholera epidemic was already on the wane when he
+did so, it is possible that the disabling of the pump prevented many deaths from
+future waves of the disease.
+
+The removal of the Broad Street pump handle has become the stuff of legend. At
+the Centers for Disease Control (CDC) in Atlanta, when scientists look for
+simple answers to questions about epidemics, they sometimes ask each other,
+“Where is the handle to this pump?”
+
+Snow’s map is one of the earliest and most powerful uses of data visualization.
+Disease maps of various kinds are now a standard tool for tracking epidemics.
+
+**Towards Causality**
+
+Though the map gave Snow a strong indication that  the cleanliness of the water
+supply was the key to controlling cholera, he was still a long way from a
+convincing scientific argument that contaminated water was causing the spread of
+the disease. To make a more compelling case, he had to use the method of
+*comparison*.
+
+Scientists use comparison to identify an association between a treatment and an
+outcome. They compare the outcomes of a group of individuals who got the
+treatment (the *treatment group*) to the outcomes of a group who did not (the
+*control group*). For example, researchers today might compare the average
+murder rate in states that have the death penalty with the average murder rate
+in states that don’t.
+
+If the results are different, that is evidence for an association. To determine
+causation, however, even more care is needed.

02/2/.ipynb_checkpoints/snow-s-grand-experiment-checkpoint.md

@@ -0,0 +1,37 @@
+# Snow’s “Grand Experiment”
+Encouraged by what he had learned in Soho, Snow completed a more thorough
+analysis. For some time, he had been gathering data on cholera
+deaths in an area of London that was served by two water companies. The Lambeth
+water company drew its water upriver from where sewage was discharged into the
+River Thames. Its water was relatively clean. But the Southwark and Vauxhall
+(S&V) company drew its water below the sewage discharge, and thus its supply was
+contaminated.
+
+The map below shows the areas served by the two companies. Snow honed in on the region where the two service areas overlap.
+![Snow’s Other Map](../../images/snow_map2.jpg)
+
+Snow noticed that there was no systematic difference between the people who were
+supplied by S&V and those supplied by Lambeth. “Each company supplies both rich
+and poor, both large houses and small; there is no difference either in the
+condition or occupation of the persons receiving the water of the different
+Companies … there is no difference whatever in the houses or the people
+receiving the supply of the two Water Companies, or in any of the physical
+conditions with which they are surrounded …”
+
+The only difference was in the water supply, “one group being supplied with
+water containing the sewage of London, and amongst it, whatever might have come
+from the cholera patients, the other group having water quite free from
+impurity.”
+
+Confident that he would be able to arrive at a clear conclusion, Snow summarized
+his data in the table below.
+
+| Supply Area    | Number of houses | cholera deaths | deaths per 10,000 houses |
+|----------------|------------------|----------------|--------------------------|
+| S&V            | 40,046           | 1,263          | 315                      |
+| Lambeth        | 26,107           | 98             | 37                       |
+| Rest of London | 256,423          | 1,422          | 59                       |
+
+
+The numbers pointed accusingly at S&V. The death rate from cholera in the S&V
+houses was almost ten times the rate in the houses supplied by Lambeth.

02/2/snow-s-grand-experiment.md

@@ -0,0 +1,37 @@
+# Snow’s “Grand Experiment”
+Encouraged by what he had learned in Soho, Snow completed a more thorough
+analysis. For some time, he had been gathering data on cholera
+deaths in an area of London that was served by two water companies. The Lambeth
+water company drew its water upriver from where sewage was discharged into the
+River Thames. Its water was relatively clean. But the Southwark and Vauxhall
+(S&V) company drew its water below the sewage discharge, and thus its supply was
+contaminated.
+
+The map below shows the areas served by the two companies. Snow honed in on the region where the two service areas overlap.
+![Snow’s Other Map](../../images/snow_map2.jpg)
+
+Snow noticed that there was no systematic difference between the people who were
+supplied by S&V and those supplied by Lambeth. “Each company supplies both rich
+and poor, both large houses and small; there is no difference either in the
+condition or occupation of the persons receiving the water of the different
+Companies … there is no difference whatever in the houses or the people
+receiving the supply of the two Water Companies, or in any of the physical
+conditions with which they are surrounded …”
+
+The only difference was in the water supply, “one group being supplied with
+water containing the sewage of London, and amongst it, whatever might have come
+from the cholera patients, the other group having water quite free from
+impurity.”
+
+Confident that he would be able to arrive at a clear conclusion, Snow summarized
+his data in the table below.
+
+| Supply Area    | Number of houses | cholera deaths | deaths per 10,000 houses |
+|----------------|------------------|----------------|--------------------------|
+| S&V            | 40,046           | 1,263          | 315                      |
+| Lambeth        | 26,107           | 98             | 37                       |
+| Rest of London | 256,423          | 1,422          | 59                       |
+
+
+The numbers pointed accusingly at S&V. The death rate from cholera in the S&V
+houses was almost ten times the rate in the houses supplied by Lambeth.

02/3/.ipynb_checkpoints/establishing-causality-checkpoint.md

@@ -0,0 +1,57 @@
+# Establishing Causality
+In the language developed earlier in the section, you can think of the people in
+the S&V houses as the treatment group, and those in the Lambeth houses at the
+control group. A crucial element in Snow’s analysis was that the people in the
+two groups were comparable to each other, apart from the treatment.
+
+In order to establish whether it was the water supply that was causing cholera,
+Snow had to compare two groups that were similar to each other in all but one
+aspect—their water supply. Only then would he be able to ascribe the differences
+in their outcomes to the water supply. If the two groups had been different in
+some other way as well, it would have been difficult to point the finger at the
+water supply as the source of the disease.  For example, if the treatment group
+consisted of factory workers and the control group did not, then differences
+between the outcomes in the two groups could have been due to the water supply,
+or to factory work, or both. The final picture would have been much more fuzzy.
+
+Snow’s brilliance lay in identifying two groups that would make his comparison
+clear. He had set out to establish a causal relation between contaminated water
+and cholera infection, and to a great extent he succeeded, even though the
+miasmatists ignored and even ridiculed him. Of course, Snow did not understand
+the detailed mechanism by which humans contract cholera. That discovery was made
+in 1883, when the German scientist Robert Koch isolated the *Vibrio cholerae*,
+the bacterium that enters the human small intestine and causes cholera.
+
+In fact the *Vibrio cholerae* had been identified in 1854 by Filippo Pacini in
+Italy, just about when Snow was analyzing his data in London. Because of the
+dominance of the miasmatists in Italy, Pacini’s discovery languished unknown.
+But by the end of the 1800’s, the miasma brigade was in retreat. Subsequent
+history has vindicated Pacini and John Snow. Snow’s methods led to the
+development of the field of *epidemiology*, which is the study of the spread of
+diseases.
+
+**Confounding**
+
+Let us now return to more modern times, armed with an important lesson that we
+have learned along the way:
+
+**In an observational study, if the treatment and control groups differ in ways
+other than the treatment, it is difficult to make conclusions about causality.**
+
+An underlying difference between the two groups (other than the treatment) is
+called a *confounding factor*, because it might confound you (that is, mess you
+up) when you try to reach a conclusion.
+
+**Example: Coffee and lung cancer.** Studies in the 1960’s showed that coffee
+drinkers had higher rates of lung cancer than those who did not drink coffee.
+Because of this, some people identified coffee as a cause of lung cancer. But
+coffee does not cause lung cancer. The analysis contained a confounding factor—smoking. In those days, coffee drinkers were also likely to have been smokers,
+and smoking does cause lung cancer. Coffee drinking was associated with lung
+cancer, but it did not cause the disease.
+
+Confounding factors are common in observational studies. Good studies take great
+care to reduce confounding and to account for its effects.
+
+```python
+
+```

02/3/establishing-causality.md

@@ -0,0 +1,57 @@
+# Establishing Causality
+In the language developed earlier in the section, you can think of the people in
+the S&V houses as the treatment group, and those in the Lambeth houses at the
+control group. A crucial element in Snow’s analysis was that the people in the
+two groups were comparable to each other, apart from the treatment.
+
+In order to establish whether it was the water supply that was causing cholera,
+Snow had to compare two groups that were similar to each other in all but one
+aspect—their water supply. Only then would he be able to ascribe the differences
+in their outcomes to the water supply. If the two groups had been different in
+some other way as well, it would have been difficult to point the finger at the
+water supply as the source of the disease.  For example, if the treatment group
+consisted of factory workers and the control group did not, then differences
+between the outcomes in the two groups could have been due to the water supply,
+or to factory work, or both. The final picture would have been much more fuzzy.
+
+Snow’s brilliance lay in identifying two groups that would make his comparison
+clear. He had set out to establish a causal relation between contaminated water
+and cholera infection, and to a great extent he succeeded, even though the
+miasmatists ignored and even ridiculed him. Of course, Snow did not understand
+the detailed mechanism by which humans contract cholera. That discovery was made
+in 1883, when the German scientist Robert Koch isolated the *Vibrio cholerae*,
+the bacterium that enters the human small intestine and causes cholera.
+
+In fact the *Vibrio cholerae* had been identified in 1854 by Filippo Pacini in
+Italy, just about when Snow was analyzing his data in London. Because of the
+dominance of the miasmatists in Italy, Pacini’s discovery languished unknown.
+But by the end of the 1800’s, the miasma brigade was in retreat. Subsequent
+history has vindicated Pacini and John Snow. Snow’s methods led to the
+development of the field of *epidemiology*, which is the study of the spread of
+diseases.
+
+**Confounding**
+
+Let us now return to more modern times, armed with an important lesson that we
+have learned along the way:
+
+**In an observational study, if the treatment and control groups differ in ways
+other than the treatment, it is difficult to make conclusions about causality.**
+
+An underlying difference between the two groups (other than the treatment) is
+called a *confounding factor*, because it might confound you (that is, mess you
+up) when you try to reach a conclusion.
+
+**Example: Coffee and lung cancer.** Studies in the 1960’s showed that coffee
+drinkers had higher rates of lung cancer than those who did not drink coffee.
+Because of this, some people identified coffee as a cause of lung cancer. But
+coffee does not cause lung cancer. The analysis contained a confounding factor—smoking. In those days, coffee drinkers were also likely to have been smokers,
+and smoking does cause lung cancer. Coffee drinking was associated with lung
+cancer, but it did not cause the disease.
+
+Confounding factors are common in observational studies. Good studies take great
+care to reduce confounding and to account for its effects.
+
+```python
+
+```

02/4/.ipynb_checkpoints/randomization-checkpoint.md

@@ -0,0 +1,48 @@
+# Randomization
+An excellent way to avoid confounding is to assign individuals to the treatment
+and control groups *at random*, and then administer the treatment to those who
+were assigned to the treatment group. Randomization keeps the two groups similar
+apart from the treatment.
+
+If you are able to randomize individuals into the treatment and control groups,
+you are running a *randomized controlled experiment*, also known as a
+*randomized controlled trial* (RCT). Sometimes, people’s responses in an
+experiment are influenced by their knowing which group they are in. So you might
+want to run a *blind* experiment in which individuals do not know whether they
+are in the treatment group or the control group. To make this work, you will
+have to give the control group a *placebo*, which is something that looks
+exactly like the treatment but in fact has no effect.
+
+Randomized controlled experiments have long been a gold standard in the medical
+field, for example in establishing whether a new drug works. They are also
+becoming more commonly used in other fields such as economics.
+
+**Example: Welfare subsidies in Mexico.** In Mexican villages in the 1990’s,
+children in poor families were often not enrolled in school. One of the reasons
+was that the older children could go to work and thus help support the family.
+Santiago Levy , a minister in Mexican Ministry of Finance, set out to
+investigate whether welfare programs could be used to increase school enrollment
+and improve health conditions. He conducted an RCT on a set of villages,
+selecting some of them at random to receive a new welfare program called
+PROGRESA. The program gave money to poor families if their children went to
+school regularly and the family used preventive health care. More money was
+given if the children were in secondary school than in primary school, to
+compensate for the children’s lost wages, and more money was given for girls
+attending school than for boys. The remaining villages did not get this
+treatment, and formed the control group. Because of the randomization, there
+were no confounding factors and it was possible to establish that PROGRESA
+increased school enrollment. For boys, the enrollment increased from 73% in the
+control group to 77% in the PROGRESA group. For girls, the increase was even
+greater, from 67% in the control group to almost 75% in the PROGRESA group. Due
+to the success of this experiment, the Mexican government supported the program
+under the new name OPORTUNIDADES, as an investment in a healthy and well
+educated population.
+
+
+In some situations it might not be possible to carry out a randomized controlled
+experiment, even when the aim is to investigate causality. For example, suppose
+you want to study the effects of alcohol consumption during pregnancy, and you
+randomly assign some pregnant women to your “alcohol” group. You should not
+expect cooperation from them if you present them with a drink. In such
+situations you will almost invariably be conducting an observational study, not
+an experiment. Be alert for confounding factors.

02/4/randomization.md

@@ -0,0 +1,48 @@
+# Randomization
+An excellent way to avoid confounding is to assign individuals to the treatment
+and control groups *at random*, and then administer the treatment to those who
+were assigned to the treatment group. Randomization keeps the two groups similar
+apart from the treatment.
+
+If you are able to randomize individuals into the treatment and control groups,
+you are running a *randomized controlled experiment*, also known as a
+*randomized controlled trial* (RCT). Sometimes, people’s responses in an
+experiment are influenced by their knowing which group they are in. So you might
+want to run a *blind* experiment in which individuals do not know whether they
+are in the treatment group or the control group. To make this work, you will
+have to give the control group a *placebo*, which is something that looks
+exactly like the treatment but in fact has no effect.
+
+Randomized controlled experiments have long been a gold standard in the medical
+field, for example in establishing whether a new drug works. They are also
+becoming more commonly used in other fields such as economics.
+
+**Example: Welfare subsidies in Mexico.** In Mexican villages in the 1990’s,
+children in poor families were often not enrolled in school. One of the reasons
+was that the older children could go to work and thus help support the family.
+Santiago Levy , a minister in Mexican Ministry of Finance, set out to
+investigate whether welfare programs could be used to increase school enrollment
+and improve health conditions. He conducted an RCT on a set of villages,
+selecting some of them at random to receive a new welfare program called
+PROGRESA. The program gave money to poor families if their children went to
+school regularly and the family used preventive health care. More money was
+given if the children were in secondary school than in primary school, to
+compensate for the children’s lost wages, and more money was given for girls
+attending school than for boys. The remaining villages did not get this
+treatment, and formed the control group. Because of the randomization, there
+were no confounding factors and it was possible to establish that PROGRESA
+increased school enrollment. For boys, the enrollment increased from 73% in the
+control group to 77% in the PROGRESA group. For girls, the increase was even
+greater, from 67% in the control group to almost 75% in the PROGRESA group. Due
+to the success of this experiment, the Mexican government supported the program
+under the new name OPORTUNIDADES, as an investment in a healthy and well
+educated population.
+
+
+In some situations it might not be possible to carry out a randomized controlled
+experiment, even when the aim is to investigate causality. For example, suppose
+you want to study the effects of alcohol consumption during pregnancy, and you
+randomly assign some pregnant women to your “alcohol” group. You should not
+expect cooperation from them if you present them with a drink. In such
+situations you will almost invariably be conducting an observational study, not
+an experiment. Be alert for confounding factors.

02/5/.ipynb_checkpoints/endnote-checkpoint.md

@@ -0,0 +1,82 @@
+# Endnote
+In the terminology that we have developed, John Snow conducted an
+observational study, not a randomized experiment. But he called his study a
+“grand experiment” because, as he wrote, “No fewer than three hundred thousand
+people … were divided into two groups without their choice, and in most cases,
+without their knowledge …”
+
+Studies such as Snow’s are sometimes called “natural experiments.” However, true
+randomization does not simply mean that the treatment and control groups are
+selected “without their choice.”
+
+The method of randomization can be as simple as tossing a coin. It may also be
+quite a bit more complex. But every method of randomization consists of a
+sequence of carefully defined steps that allow chances to be specified
+mathematically. This has two important consequences.
+
+1. It allows us to account—mathematically—for the possibility that randomization
+   produces treatment and control groups that are quite different from each
+   other.
+
+2. It allows us to make precise mathematical statements about differences
+   between the treatment and control groups. This in turn helps us make
+   justifiable conclusions about whether the treatment has any effect.
+
+
+In this course, you will learn how to conduct and analyze your own randomized
+experiments. That will involve more detail than has been presented in this
+chapter. For now, just focus on the main idea: to try to establish causality,
+run a randomized controlled experiment if possible. If you are conducting an
+observational study, you might be able to establish association but it will be harder to establish causation. Be extremely careful about confounding factors before making
+conclusions about causality based on an observational study.
+
+**Terminology**
+
+* observational study
+* treatment
+* outcome
+* association
+* causal association
+* causality
+* comparison
+* treatment group
+* control group
+* epidemiology
+* confounding
+* randomization
+* randomized controlled experiment
+* randomized controlled trial (RCT)
+* blind
+* placebo
+
+**Fun facts**
+
+1. John Snow is sometimes called the father of epidemiology, but he was an
+   anesthesiologist by profession. One of his patients was Queen Victoria, who
+   was an early recipient of anesthetics during childbirth.
+
+2. Florence Nightingale, the originator of modern nursing practices and famous
+   for her work in the Crimean War, was a die-hard miasmatist. She had no time
+   for theories about contagion and germs, and was not one for mincing her
+   words. “There is no end to the absurdities connected with this doctrine,” she
+   said. “Suffice it to say that in the ordinary sense of the word, there is no
+   proof such as would be admitted in any scientific enquiry that there is any
+   such thing as contagion.”
+
+3. A later RCT established that the conditions on which PROGRESA insisted—children
+   going to school, preventive health care—were not necessary to
+   achieve increased enrollment. Just the financial boost of the welfare
+   payments was sufficient.
+
+
+**Good reads**
+
+[*The Strange Case of the Broad Street Pump: John Snow and the Mystery of
+Cholera*](http://www.ucpress.edu/book.php?isbn=9780520250499) by Sandra Hempel,
+published by our own University of California Press, reads like a whodunit. It
+was one of the main sources for this section's account of John Snow and his
+work. A word of warning: some of the contents of the book are stomach-churning.
+
+[*Poor Economics*](http://www.pooreconomics.com), the best seller by Abhijit Banerjee and Esther Duflo of MIT, is an accessible and lively account of ways to
+fight global poverty. It includes numerous examples of RCTs, including the
+PROGRESA example in this section.

02/5/endnote.md

@@ -0,0 +1,82 @@
+# Endnote
+In the terminology that we have developed, John Snow conducted an
+observational study, not a randomized experiment. But he called his study a
+“grand experiment” because, as he wrote, “No fewer than three hundred thousand
+people … were divided into two groups without their choice, and in most cases,
+without their knowledge …”
+
+Studies such as Snow’s are sometimes called “natural experiments.” However, true
+randomization does not simply mean that the treatment and control groups are
+selected “without their choice.”
+
+The method of randomization can be as simple as tossing a coin. It may also be
+quite a bit more complex. But every method of randomization consists of a
+sequence of carefully defined steps that allow chances to be specified
+mathematically. This has two important consequences.
+
+1. It allows us to account—mathematically—for the possibility that randomization
+   produces treatment and control groups that are quite different from each
+   other.
+
+2. It allows us to make precise mathematical statements about differences
+   between the treatment and control groups. This in turn helps us make
+   justifiable conclusions about whether the treatment has any effect.
+
+
+In this course, you will learn how to conduct and analyze your own randomized
+experiments. That will involve more detail than has been presented in this
+chapter. For now, just focus on the main idea: to try to establish causality,
+run a randomized controlled experiment if possible. If you are conducting an
+observational study, you might be able to establish association but it will be harder to establish causation. Be extremely careful about confounding factors before making
+conclusions about causality based on an observational study.
+
+**Terminology**
+
+* observational study
+* treatment
+* outcome
+* association
+* causal association
+* causality
+* comparison
+* treatment group
+* control group
+* epidemiology
+* confounding
+* randomization
+* randomized controlled experiment
+* randomized controlled trial (RCT)
+* blind
+* placebo
+
+**Fun facts**
+
+1. John Snow is sometimes called the father of epidemiology, but he was an
+   anesthesiologist by profession. One of his patients was Queen Victoria, who
+   was an early recipient of anesthetics during childbirth.
+
+2. Florence Nightingale, the originator of modern nursing practices and famous
+   for her work in the Crimean War, was a die-hard miasmatist. She had no time
+   for theories about contagion and germs, and was not one for mincing her
+   words. “There is no end to the absurdities connected with this doctrine,” she
+   said. “Suffice it to say that in the ordinary sense of the word, there is no
+   proof such as would be admitted in any scientific enquiry that there is any
+   such thing as contagion.”
+
+3. A later RCT established that the conditions on which PROGRESA insisted—children
+   going to school, preventive health care—were not necessary to
+   achieve increased enrollment. Just the financial boost of the welfare
+   payments was sufficient.
+
+
+**Good reads**
+
+[*The Strange Case of the Broad Street Pump: John Snow and the Mystery of
+Cholera*](http://www.ucpress.edu/book.php?isbn=9780520250499) by Sandra Hempel,
+published by our own University of California Press, reads like a whodunit. It
+was one of the main sources for this section's account of John Snow and his
+work. A word of warning: some of the contents of the book are stomach-churning.
+
+[*Poor Economics*](http://www.pooreconomics.com), the best seller by Abhijit Banerjee and Esther Duflo of MIT, is an accessible and lively account of ways to
+fight global poverty. It includes numerous examples of RCTs, including the
+PROGRESA example in this section.

02/causality-and-experiments.md

@@ -0,0 +1,38 @@
+# 2. Causality and Experiments
+*"These problems are, and will probably ever remain, among the inscrutable
+secrets of nature. They belong to a class of questions radically inaccessible to
+the human intelligence."* —The Times of London, September 1849, on how cholera
+is contracted and spread
+
+Does the death penalty have a deterrent effect? Is chocolate good for you? What
+causes breast cancer?
+
+All of these questions attempt to assign a cause to an effect. A careful
+examination of data can help shed light on questions like these. In this section
+you will learn some of the fundamental concepts involved in establishing
+causality.
+
+Observation is a key to good science. An *observational study* is one in which
+scientists make conclusions based on data that they have observed but had no
+hand in generating. In data science, many such studies involve observations on a
+group of individuals, a factor of interest called a *treatment*, and an
+*outcome* measured on each individual.
+
+It is easiest to think of the individuals as people. In a study of whether
+chocolate is good for the health, the individuals would indeed be people, the
+treatment would be eating chocolate, and the outcome might be a measure of heart disease. But individuals in observational studies need not be people. In a
+study of whether the death penalty has a deterrent effect, the individuals could
+be the 50 states of the union. A state law allowing the death penalty would be
+the treatment, and an outcome could be the state’s murder rate.
+
+The fundamental question is whether the treatment has an effect on the outcome.
+Any relation between the treatment and the outcome is called an *association*.
+If the treatment causes the outcome to occur, then the association is *causal*.
+*Causality* is at the heart of all three questions posed at the start of this
+section. For example, one of the questions was whether chocolate directly causes
+improvements in health, not just whether there there is a relation between
+chocolate and health.
+
+The establishment of causality often takes place in two stages. First, an
+association is observed. Next, a more careful analysis leads to a decision about
+causality.

03/1/.ipynb_checkpoints/Expressions-checkpoint.ipynb

@@ -0,0 +1,190 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Expressions\n",
+    "\n",
+    "Programming languages are much simpler than human languages. Nonetheless, there are some rules of grammar to learn in any language, and that is where we will begin. In this text, we will use the [Python](https://www.python.org/) programming language. Learning the grammar rules is essential, and the same rules used in the most basic programs are also central to more sophisticated programs.\n",
+    "\n",
+    "Programs are made up of *expressions*, which describe to the computer how to combine pieces of data. For example, a multiplication expression consists of a `*` symbol between two numerical expressions. Expressions, such as `3 * 4`, are *evaluated* by the computer. The value (the result of *evaluation*) of the last expression in each cell, `12` in this case, is displayed below the cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 * 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The grammar rules of a programming language are rigid. In Python, the `*` symbol cannot appear twice in a row. The computer will not try to interpret an expression that differs from its prescribed expression structures. Instead, it will show a `SyntaxError` error. The *Syntax* of a language is its set of grammar rules, and a `SyntaxError` indicates that an expression structure doesn't match any of the rules of the language."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": [
+     "raises-exception"
+    ]
+   },
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (<ipython-input-2-012ea60b41dd>, line 1)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-2-012ea60b41dd>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    3 * * 4\u001b[0m\n\u001b[0m        ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
+   "source": [
+    "3 * * 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Small changes to an expression can change its meaning entirely. Below, the space between the `*`'s has been removed. Because `**` appears between two numerical expressions, the expression is a well-formed *exponentiation* expression (the first number raised to the power of the second: 3 times 3 times 3 times 3). The symbols `*` and `**` are called *operators*, and the values they combine are called *operands*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "81"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 ** 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Common Operators.** Data science often involves combining numerical values, and the set of operators in a programming language are designed to so that expressions can be used to express any sort of arithmetic. In Python, the following operators are essential.\n",
+    "\n",
+    "| Expression Type | Operator | Example    | Value     |\n",
+    "|-----------------|----------|------------|-----------|\n",
+    "| Addition        | `+`      | `2 + 3`    | `5`       |\n",
+    "| Subtraction     | `-`      | `2 - 3`    | `-1`      |\n",
+    "| Multiplication  | `*`      | `2 * 3`    | `6`       |\n",
+    "| Division        | `/`      | `7 / 3`    | `2.66667` |\n",
+    "| Remainder       | `%`      | `7 % 3`    | `1`       |\n",
+    "| Exponentiation  | `**`     | `2 ** 0.5` | `1.41421` |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Python expressions obey the same familiar rules of *precedence* as in algebra: multiplication and division occur before addition and subtraction. Parentheses can be used to group together smaller expressions within a larger expression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "17.555555555555557"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 + 2 * 3 * 4 * 5 / 6 ** 3 + 7 + 8 - 9 + 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2017.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 + 2 * (3 * 4 * 5 / 6) ** 3 + 7 + 8 - 9 + 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This chapter introduces many types of expressions. Learning to program involves trying out everything you learn in combination, investigating the behavior of the computer. What happens if you divide by zero? What happens if you divide twice in a row? You don't always need to ask an expert (or the Internet); many of these details can be discovered by trying them out yourself. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/1/Expressions.ipynb

@@ -0,0 +1,190 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Expressions\n",
+    "\n",
+    "Programming languages are much simpler than human languages. Nonetheless, there are some rules of grammar to learn in any language, and that is where we will begin. In this text, we will use the [Python](https://www.python.org/) programming language. Learning the grammar rules is essential, and the same rules used in the most basic programs are also central to more sophisticated programs.\n",
+    "\n",
+    "Programs are made up of *expressions*, which describe to the computer how to combine pieces of data. For example, a multiplication expression consists of a `*` symbol between two numerical expressions. Expressions, such as `3 * 4`, are *evaluated* by the computer. The value (the result of *evaluation*) of the last expression in each cell, `12` in this case, is displayed below the cell."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 * 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The grammar rules of a programming language are rigid. In Python, the `*` symbol cannot appear twice in a row. The computer will not try to interpret an expression that differs from its prescribed expression structures. Instead, it will show a `SyntaxError` error. The *Syntax* of a language is its set of grammar rules, and a `SyntaxError` indicates that an expression structure doesn't match any of the rules of the language."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": [
+     "raises-exception"
+    ]
+   },
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (<ipython-input-2-012ea60b41dd>, line 1)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-2-012ea60b41dd>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    3 * * 4\u001b[0m\n\u001b[0m        ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
+   "source": [
+    "3 * * 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Small changes to an expression can change its meaning entirely. Below, the space between the `*`'s has been removed. Because `**` appears between two numerical expressions, the expression is a well-formed *exponentiation* expression (the first number raised to the power of the second: 3 times 3 times 3 times 3). The symbols `*` and `**` are called *operators*, and the values they combine are called *operands*."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "81"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 ** 4"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Common Operators.** Data science often involves combining numerical values, and the set of operators in a programming language are designed to so that expressions can be used to express any sort of arithmetic. In Python, the following operators are essential.\n",
+    "\n",
+    "| Expression Type | Operator | Example    | Value     |\n",
+    "|-----------------|----------|------------|-----------|\n",
+    "| Addition        | `+`      | `2 + 3`    | `5`       |\n",
+    "| Subtraction     | `-`      | `2 - 3`    | `-1`      |\n",
+    "| Multiplication  | `*`      | `2 * 3`    | `6`       |\n",
+    "| Division        | `/`      | `7 / 3`    | `2.66667` |\n",
+    "| Remainder       | `%`      | `7 % 3`    | `1`       |\n",
+    "| Exponentiation  | `**`     | `2 ** 0.5` | `1.41421` |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Python expressions obey the same familiar rules of *precedence* as in algebra: multiplication and division occur before addition and subtraction. Parentheses can be used to group together smaller expressions within a larger expression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "17.555555555555557"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 + 2 * 3 * 4 * 5 / 6 ** 3 + 7 + 8 - 9 + 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2017.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 + 2 * (3 * 4 * 5 / 6) ** 3 + 7 + 8 - 9 + 10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This chapter introduces many types of expressions. Learning to program involves trying out everything you learn in combination, investigating the behavior of the computer. What happens if you divide by zero? What happens if you divide twice in a row? You don't always need to ask an expert (or the Internet); many of these details can be discovered by trying them out yourself. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/2/.ipynb_checkpoints/Names-checkpoint.ipynb

@@ -0,0 +1,147 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Names\n",
+    "\n",
+    "Names are given to values in Python using an *assignment* statement. In an assignment, a name is followed by `=`, which is followed by any expression. The value of the expression to the right of `=` is *assigned* to the name. Once a name has a value assigned to it, the value will be substituted for that name in future expressions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "30"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a = 10\n",
+    "b = 20\n",
+    "a + b"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A previously assigned name can be used in the expression to the right of `=`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "quarter = 1/4\n",
+    "half = 2 * quarter\n",
+    "half"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "However, only the current value of an expression is assigned to a name. If that value changes later, names that were defined in terms of that value will not change automatically."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "quarter = 4\n",
+    "half"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Names must start with a letter, but can contain both letters and numbers. A name cannot contain a space; instead, it is common to use an underscore character `_` to replace each space. Names are only as useful as you make them; it's up to the programmer to choose names that are easy to interpret. Typically, more meaningful names can be invented than `a` and `b`. For example, to describe the sales tax on a $5 purchase in Berkeley, CA, the following names clarify the meaning of the various quantities involved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.475"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "purchase_price = 5\n",
+    "state_tax_rate = 0.075\n",
+    "county_tax_rate = 0.02\n",
+    "city_tax_rate = 0\n",
+    "sales_tax_rate = state_tax_rate + county_tax_rate + city_tax_rate\n",
+    "sales_tax = purchase_price * sales_tax_rate\n",
+    "sales_tax"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/2/1/.ipynb_checkpoints/Growth-checkpoint.ipynb

@@ -0,0 +1,307 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Example: Growth Rates\n",
+    "\n",
+    "The relationship between two measurements of the same quantity taken at different times is often expressed as a *growth rate*. For example, the United States federal government [employed](http://www.bls.gov/opub/mlr/2013/article/industry-employment-and-output-projections-to-2022-1.htm) 2,766,000 people in 2002 and 2,814,000 people in 2012. To compute a growth rate, we must first decide which value to treat as the `initial` amount. For values over time, the earlier value is a natural choice. Then, we divide the difference between the `changed` and `initial` amount by the `initial` amount."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.01735357917570499"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2766000\n",
+    "changed = 2814000\n",
+    "(changed - initial) / initial"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is also typical to subtract one from the ratio of the two measurements, which yields the same value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.017353579175704903"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This value is the growth rate over 10 years. A useful property of growth rates is that they don't change even if the values are expressed in different units. So, for example, we can express the same relationship between thousands of people in 2002 and 2012."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.017353579175704903"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2766\n",
+    "changed = 2814\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In 10 years, the number of employees of the US Federal Government has increased by only 1.74%. In that time, the total expenditures of the US Federal Government increased from \\$2.37 trillion to \\$3.38 trillion in 2012."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.4261603375527425"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2.37\n",
+    "changed = 3.38\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A 42.6% increase in the federal budget is much larger than the 1.74% increase in federal employees. In fact, the number of federal employees has grown much more slowly than the population of the United States, which increased 9.21% in the same time period from 287.6 million people in 2002 to 314.1 million in 2012."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.09214186369958277"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 287.6\n",
+    "changed = 314.1\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A growth rate can be negative, representing a decrease in some value. For example, the number of manufacturing jobs in the US decreased from 15.3 million in 2002 to 11.9 million in 2012, a -22.2% growth rate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.2222222222222222"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 15.3\n",
+    "changed = 11.9\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An annual growth rate is a growth rate of some quantity over a single year. An annual growth rate of 0.035, accumulated each year for 10 years, gives a much larger ten-year growth rate of 0.41 (or 41%)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.410598760621121"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This same computation can be expressed using names and exponents."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.410598760621121"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "annual_growth_rate = 0.035\n",
+    "ten_year_growth_rate = (1 + annual_growth_rate) ** 10 - 1\n",
+    "ten_year_growth_rate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Likewise, a ten-year growth rate can be used to compute an equivalent annual growth rate. Below, `t` is the number of years that have passed between measurements. The following computes the annual growth rate of federal expenditures over the last 10 years."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.03613617208346853"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2.37\n",
+    "changed = 3.38\n",
+    "t = 10\n",
+    "(changed/initial) ** (1/t) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The total growth over 10 years is equivalent to a 3.6% increase each year."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In summary, a growth rate `g` is used to describe the relative size of an `initial` amount and a `changed` amount after some amount of time `t`. To compute $changed$, apply the growth rate `g` repeatedly, `t` times using exponentiation.\n",
+    "\n",
+    "`initial * (1 + g) ** t`\n",
+    "\n",
+    "To compute `g`, raise the total growth to the power of `1/t` and subtract one.\n",
+    "\n",
+    "`(changed/initial) ** (1/t) - 1`"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/2/1/Growth.ipynb

@@ -0,0 +1,307 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Example: Growth Rates\n",
+    "\n",
+    "The relationship between two measurements of the same quantity taken at different times is often expressed as a *growth rate*. For example, the United States federal government [employed](http://www.bls.gov/opub/mlr/2013/article/industry-employment-and-output-projections-to-2022-1.htm) 2,766,000 people in 2002 and 2,814,000 people in 2012. To compute a growth rate, we must first decide which value to treat as the `initial` amount. For values over time, the earlier value is a natural choice. Then, we divide the difference between the `changed` and `initial` amount by the `initial` amount."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.01735357917570499"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2766000\n",
+    "changed = 2814000\n",
+    "(changed - initial) / initial"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is also typical to subtract one from the ratio of the two measurements, which yields the same value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.017353579175704903"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This value is the growth rate over 10 years. A useful property of growth rates is that they don't change even if the values are expressed in different units. So, for example, we can express the same relationship between thousands of people in 2002 and 2012."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.017353579175704903"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2766\n",
+    "changed = 2814\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In 10 years, the number of employees of the US Federal Government has increased by only 1.74%. In that time, the total expenditures of the US Federal Government increased from \\$2.37 trillion to \\$3.38 trillion in 2012."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.4261603375527425"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2.37\n",
+    "changed = 3.38\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A 42.6% increase in the federal budget is much larger than the 1.74% increase in federal employees. In fact, the number of federal employees has grown much more slowly than the population of the United States, which increased 9.21% in the same time period from 287.6 million people in 2002 to 314.1 million in 2012."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.09214186369958277"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 287.6\n",
+    "changed = 314.1\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A growth rate can be negative, representing a decrease in some value. For example, the number of manufacturing jobs in the US decreased from 15.3 million in 2002 to 11.9 million in 2012, a -22.2% growth rate."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.2222222222222222"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 15.3\n",
+    "changed = 11.9\n",
+    "(changed/initial) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An annual growth rate is a growth rate of some quantity over a single year. An annual growth rate of 0.035, accumulated each year for 10 years, gives a much larger ten-year growth rate of 0.41 (or 41%)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.410598760621121"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 * 1.035 - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This same computation can be expressed using names and exponents."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.410598760621121"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "annual_growth_rate = 0.035\n",
+    "ten_year_growth_rate = (1 + annual_growth_rate) ** 10 - 1\n",
+    "ten_year_growth_rate"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Likewise, a ten-year growth rate can be used to compute an equivalent annual growth rate. Below, `t` is the number of years that have passed between measurements. The following computes the annual growth rate of federal expenditures over the last 10 years."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.03613617208346853"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = 2.37\n",
+    "changed = 3.38\n",
+    "t = 10\n",
+    "(changed/initial) ** (1/t) - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The total growth over 10 years is equivalent to a 3.6% increase each year."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In summary, a growth rate `g` is used to describe the relative size of an `initial` amount and a `changed` amount after some amount of time `t`. To compute $changed$, apply the growth rate `g` repeatedly, `t` times using exponentiation.\n",
+    "\n",
+    "`initial * (1 + g) ** t`\n",
+    "\n",
+    "To compute `g`, raise the total growth to the power of `1/t` and subtract one.\n",
+    "\n",
+    "`(changed/initial) ** (1/t) - 1`"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/2/Names.ipynb

@@ -0,0 +1,147 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Names\n",
+    "\n",
+    "Names are given to values in Python using an *assignment* statement. In an assignment, a name is followed by `=`, which is followed by any expression. The value of the expression to the right of `=` is *assigned* to the name. Once a name has a value assigned to it, the value will be substituted for that name in future expressions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "30"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "a = 10\n",
+    "b = 20\n",
+    "a + b"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A previously assigned name can be used in the expression to the right of `=`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "quarter = 1/4\n",
+    "half = 2 * quarter\n",
+    "half"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "However, only the current value of an expression is assigned to a name. If that value changes later, names that were defined in terms of that value will not change automatically."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.5"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "quarter = 4\n",
+    "half"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Names must start with a letter, but can contain both letters and numbers. A name cannot contain a space; instead, it is common to use an underscore character `_` to replace each space. Names are only as useful as you make them; it's up to the programmer to choose names that are easy to interpret. Typically, more meaningful names can be invented than `a` and `b`. For example, to describe the sales tax on a $5 purchase in Berkeley, CA, the following names clarify the meaning of the various quantities involved."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.475"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "purchase_price = 5\n",
+    "state_tax_rate = 0.075\n",
+    "county_tax_rate = 0.02\n",
+    "city_tax_rate = 0\n",
+    "sales_tax_rate = state_tax_rate + county_tax_rate + city_tax_rate\n",
+    "sales_tax = purchase_price * sales_tax_rate\n",
+    "sales_tax"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/3/.ipynb_checkpoints/Calls-checkpoint.ipynb

@@ -0,0 +1,262 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Call Expressions\n",
+    "\n",
+    "*Call expressions* invoke functions, which are named operations. The name of the function appears first, followed by expressions in parentheses. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "abs(-12)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "round(5 - 1.3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "max(2, 2 + 3, 4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this last example, the `max` function is *called* on three *arguments*: 2, 5, and 4. The value of each expression within parentheses is passed to the function, and the function *returns* the final value of the full call expression. The `max` function can take any number of arguments and returns the maximum.\n",
+    "\n",
+    "A few functions are available by default, such as `abs` and `round`, but most functions that are built into the Python language are stored in a collection of functions called a *module*. An *import statement* is used to provide access to a module, such as `math` or `operator`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import math\n",
+    "import operator\n",
+    "math.sqrt(operator.add(4, 5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An equivalent expression could be expressed using the `+` and `**` operators instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(4 + 5) ** 0.5"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Operators and call expressions can be used together in an expression. The *percent difference* between two values is used to compare values for which neither one is obviously `initial` or `changed`. For example, in 2014 Florida farms produced 2.72 billion eggs while Iowa farms produced 16.25 billion eggs (http://quickstats.nass.usda.gov/). The percent difference is 100 times the absolute value of the difference between the values, divided by their average. In this case, the difference is larger than the average, and so the percent difference is greater than 100."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "142.6462836056932"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "florida = 2.72\n",
+    "iowa = 16.25\n",
+    "100*abs(florida-iowa)/((florida+iowa)/2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Learning how different functions behave is an important part of learning a programming language. A Jupyter notebook can assist in remembering the names and effects of different functions. When editing a code cell, press the *tab* key after typing the beginning of a name to bring up a list of ways to complete that name. For example, press *tab* after `math.` to see all of the functions available in the `math` module. Typing will narrow down the list of options. To learn more about a function, place a `?` after its name. For example, typing `math.log?` will bring up a description of the `log` function in the `math` module."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "math.log?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "    log(x[, base])\n",
+    "\n",
+    "    Return the logarithm of x to the given base.\n",
+    "    If the base not specified, returns the natural logarithm (base e) of x."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The square brackets in the example call indicate that an argument is optional. That is, `log` can be called with either one or two arguments."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "math.log(16, 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.0"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "math.log(16)/math.log(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The list of [Python's built-in functions](https://docs.python.org/3/library/functions.html) is quite long and includes many functions that are never needed in data science applications. The list of [mathematical functions in the `math` module](https://docs.python.org/3/library/math.html) is similarly long. This text will introduce the most important functions in context, rather than expecting the reader to memorize or understand these lists."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/3/Calls.ipynb

@@ -0,0 +1,262 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Call Expressions\n",
+    "\n",
+    "*Call expressions* invoke functions, which are named operations. The name of the function appears first, followed by expressions in parentheses. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "12"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "abs(-12)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "round(5 - 1.3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "max(2, 2 + 3, 4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this last example, the `max` function is *called* on three *arguments*: 2, 5, and 4. The value of each expression within parentheses is passed to the function, and the function *returns* the final value of the full call expression. The `max` function can take any number of arguments and returns the maximum.\n",
+    "\n",
+    "A few functions are available by default, such as `abs` and `round`, but most functions that are built into the Python language are stored in a collection of functions called a *module*. An *import statement* is used to provide access to a module, such as `math` or `operator`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import math\n",
+    "import operator\n",
+    "math.sqrt(operator.add(4, 5))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An equivalent expression could be expressed using the `+` and `**` operators instead."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(4 + 5) ** 0.5"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Operators and call expressions can be used together in an expression. The *percent difference* between two values is used to compare values for which neither one is obviously `initial` or `changed`. For example, in 2014 Florida farms produced 2.72 billion eggs while Iowa farms produced 16.25 billion eggs (http://quickstats.nass.usda.gov/). The percent difference is 100 times the absolute value of the difference between the values, divided by their average. In this case, the difference is larger than the average, and so the percent difference is greater than 100."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "142.6462836056932"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "florida = 2.72\n",
+    "iowa = 16.25\n",
+    "100*abs(florida-iowa)/((florida+iowa)/2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Learning how different functions behave is an important part of learning a programming language. A Jupyter notebook can assist in remembering the names and effects of different functions. When editing a code cell, press the *tab* key after typing the beginning of a name to bring up a list of ways to complete that name. For example, press *tab* after `math.` to see all of the functions available in the `math` module. Typing will narrow down the list of options. To learn more about a function, place a `?` after its name. For example, typing `math.log?` will bring up a description of the `log` function in the `math` module."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "math.log?"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "    log(x[, base])\n",
+    "\n",
+    "    Return the logarithm of x to the given base.\n",
+    "    If the base not specified, returns the natural logarithm (base e) of x."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The square brackets in the example call indicate that an argument is optional. That is, `log` can be called with either one or two arguments."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "math.log(16, 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.0"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "math.log(16)/math.log(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The list of [Python's built-in functions](https://docs.python.org/3/library/functions.html) is quite long and includes many functions that are never needed in data science applications. The list of [mathematical functions in the `math` module](https://docs.python.org/3/library/math.html) is similarly long. This text will introduce the most important functions in context, rather than expecting the reader to memorize or understand these lists."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/4/.ipynb_checkpoints/Introduction_to_Tables-checkpoint.ipynb

@@ -0,0 +1,2005 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "cones = pd.read_csv(path_data + 'cones.csv')\n",
+    "nba = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "nba.columns=['PLAYER','POSITION','TEAM','SALARY']\n",
+    "movies = pd.read_csv(path_data + 'movies_by_year.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Introduction to DataFrames\n",
+    "\n",
+    "We can now apply Python to analyze data. We will work with data stored in DataFrame structures.\n",
+    "\n",
+    "A DataFrames (df) is a fundamental way of representing data sets. A df can be viewed in two ways:\n",
+    "* a sequence of named columns that each describe a single attribute of all entries in a data set, or\n",
+    "* a sequence of rows that each contain all information about a single individual in a data set.\n",
+    "\n",
+    "We will study dfs in great detail in the next several chapters. For now, we will just introduce a few methods without going into technical details. \n",
+    "\n",
+    "The df `cones` has been imported for us; later we will see how, but here we will just work with it. First, let's take a look at it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The DataFrame has six rows. Each row corresponds to one ice cream cone. The ice cream cones are the *individuals*.\n",
+    "\n",
+    "Each cone has three attributes: flavor, color, and price. Each column contains the data on one of these attributes, and so all the entries of any single column are of the same kind. Each column has a label. We will refer to columns by their labels.\n",
+    "\n",
+    "A df method is just like a function, but it must operate on a df. So the call looks like\n",
+    "\n",
+    "`name_of_DataFrame.method(arguments)`\n",
+    "\n",
+    "For example, if you want to see just the first two rows of a df, you can use the df method `head`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.head(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can replace 2 by any number of rows. If you ask for more than six, you will only get six, because `cones` only has six rows."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Choosing Sets of Columns\n",
+    "The method `select` creates a new table consisting of only the specified columns.\n",
+    "We can state which columns we want to view by using dot '.' notation (not he same as in maths) or hard brackets with quotes. Note that an index is automatically generated, this is a fundamental aspect of the DataFrame as the index allows us to 'locate' members of the DataFrame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    strawberry\n",
+       "1     chocolate\n",
+       "2     chocolate\n",
+       "3    strawberry\n",
+       "4     chocolate\n",
+       "5     bubblegum\n",
+       "Name: Flavor, dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# single square brackets\n",
+    "\n",
+    "cones['Flavor']\n",
+    "\n",
+    "# uncomment (remove the hash mark) the line below to view the 'type()' of the output\n",
+    "\n",
+    "#type(cones['Flavor'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor\n",
+       "0  strawberry\n",
+       "1   chocolate\n",
+       "2   chocolate\n",
+       "3  strawberry\n",
+       "4   chocolate\n",
+       "5   bubblegum"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# double square brackets\n",
+    "\n",
+    "cones[['Flavor']]\n",
+    "\n",
+    "# uncomment the line below to view the 'type()' of the output\n",
+    "\n",
+    "# type(cones[['Flavor']])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    strawberry\n",
+       "1     chocolate\n",
+       "2     chocolate\n",
+       "3    strawberry\n",
+       "4     chocolate\n",
+       "5     bubblegum\n",
+       "Name: Flavor, dtype: object"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.Flavor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This leaves the original table unchanged."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25\n",
+       "5   bubblegum         pink   4.75"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can select more than one column, by separating the column labels by commas. When you wish to view more than one column the 'hard brackets' must be used twice."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   5.25\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25\n",
+       "5   bubblegum   4.75"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[['Flavor', 'Price']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can also *drop* columns you don't want. The table above can be created by dropping the `Color` column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   5.25\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25\n",
+       "5   bubblegum   4.75"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.drop(columns=['Color'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can name this new table and look at it again by just typing its name."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   5.25\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25\n",
+       "5   bubblegum   4.75"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "no_colors = cones.drop(columns=['Color'])\n",
+    "\n",
+    "no_colors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Like selecting columns using hard brackets or dot notation, the `drop` method creates a smaller table and leaves the original table unchanged. In order to explore your data, you can create any number of smaller tables by using choosing or dropping columns. It will do no harm to your original data table."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Sorting Rows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `sort_values` method creates a new table by arranging the rows of the original table in ascending order of the values in the specified column. Here the `cones` table has been sorted in ascending order of the price of the cones.\n",
+    "\n",
+    "[pandas sort_values](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_values.html#pandas-dataframe-sort-values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75\n",
+       "5   bubblegum         pink   4.75\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.sort_values('Price')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To sort in descending order, you can use an *optional* argument to `sort`. As the name implies, optional arguments don't have to be used, but they can be used if you want to change the default behavior of a method. \n",
+    "\n",
+    "By default, `sort` sorts in increasing order of the values in the specified column. To sort in decreasing order, use the optional argument `ascending=False`, the default value for `ascending` is `True`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25\n",
+       "1   chocolate  light brown   4.75\n",
+       "5   bubblegum         pink   4.75\n",
+       "0  strawberry         pink   3.55"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.sort_values('Price', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As when selecting and `drop`ing the `sort` method leaves the original table unchanged."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Selecting Rows that Satisfy a Condition\n",
+    "Creating a new DataFrame (in database world this wold be a 'view'), consisting only of the rows that satisfy a given condition we use the 'exactly equal to' `==`. In this section we will work with a very simple condition, which is that the value in a specified column must be exactly equal to a value that we also specify. Thus the `==` method has two arguments.\n",
+    "\n",
+    "The code in the cell below creates a df consisting only of the rows corresponding to chocolate cones."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Flavor        Color  Price\n",
+       "1  chocolate  light brown   4.75\n",
+       "2  chocolate   dark brown   5.25\n",
+       "4  chocolate   dark brown   5.25"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor']=='chocolate']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The arguments are the label of the column and the value we are looking for in that column. The `==` method can also be used when the condition that the rows must satisfy is more complicated. In those situations the call will be a little more complicated as well.\n",
+    "\n",
+    "It is important to provide the value exactly. For example, if we specify `Chocolate` instead of `chocolate`, then `where` correctly finds no rows where the flavor is `Chocolate`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [Flavor, Color, Price]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor'] == 'Chocolate']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Like all the other table methods in this section, `==` leaves the original table unchanged."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example: Salaries in the NBA"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\"The NBA is the highest paying professional sports league in the world,\" [reported CNN](http://edition.cnn.com/2015/12/04/sport/gallery/highest-paid-nba-players/) in March 2016. The table `nba` contains the [salaries of all National Basketball Association players](https://www.statcrunch.com/app/index.php?dataid=1843341) in 2015-2016.\n",
+    "\n",
+    "Each row represents one player. The columns are:\n",
+    "\n",
+    "| **Column Label**   | Description                                         |\n",
+    "|--------------------|-----------------------------------------------------|\n",
+    "| `PLAYER`           | Player's name                                       |\n",
+    "| `POSITION`         | Player's position on team                           |\n",
+    "| `TEAM`             | Team name                                           |\n",
+    "|`SALARY`    | Player's salary in 2015-2016, in millions of dollars|\n",
+    " \n",
+    "The code for the positions is PG (Point Guard), SG (Shooting Guard), PF (Power Forward), SF (Small Forward), and C (Center). But what follows doesn't involve details about how basketball is played.\n",
+    "\n",
+    "The first row shows that Paul Millsap, Power Forward for the Atlanta Hawks, had a salary of almost $\\$18.7$ million in 2015-2016."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM     SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks  18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks  12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks   9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks   8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks   5.746479\n",
+       "..               ...      ...                 ...        ...\n",
+       "412        Gary Neal       PG  Washington Wizards   2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards   2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards   1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards   1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards   0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Fans of Stephen Curry can find his row by using `where`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            PLAYER POSITION                   TEAM     SALARY\n",
+       "121  Stephen Curry       PG  Golden State Warriors  11.370786"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['PLAYER'] == 'Stephen Curry']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also create a new table called `warriors` consisting of just the data for the Golden State Warriors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "warriors = nba[nba['TEAM'] =='Golden State Warriors']\n",
+    "warriors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "By default, the first 10 lines of a table are displayed. You can use `head()` to display more or fewer. To display the entire table type the name of the DataFrame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "warriors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `nba` table is sorted in alphabetical order of the team names. To see how the players were paid in 2015-2016, it is useful to sort the data by salary. Remember that by default, the sorting is in increasing order."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>325</th>\n",
+       "      <td>Phil Pressey</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "325            Phil Pressey       PG         Phoenix Suns   0.055722\n",
+       "..                      ...      ...                  ...        ...\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These figures are somewhat difficult to compare as some of these players changed teams during the season and received salaries from more than one team; only the salary from the last team appears in the table.  \n",
+    "\n",
+    "The CNN report is about the other end of the salary scale – the players who are among the highest paid in the world. To identify these players we can sort in descending order of salary and look at the top few rows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>200</th>\n",
+       "      <td>Elliot Williams</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Memphis Grizzlies</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "..                      ...      ...                  ...        ...\n",
+       "200         Elliot Williams       SG    Memphis Grizzlies   0.055722\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Kobe Bryant, since retired, was the highest earning NBA player in 2015-2016."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/4/Introduction_to_Tables.ipynb

@@ -0,0 +1,2005 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "cones = pd.read_csv(path_data + 'cones.csv')\n",
+    "nba = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "nba.columns=['PLAYER','POSITION','TEAM','SALARY']\n",
+    "movies = pd.read_csv(path_data + 'movies_by_year.csv')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Introduction to DataFrames\n",
+    "\n",
+    "We can now apply Python to analyze data. We will work with data stored in DataFrame structures.\n",
+    "\n",
+    "A DataFrames (df) is a fundamental way of representing data sets. A df can be viewed in two ways:\n",
+    "* a sequence of named columns that each describe a single attribute of all entries in a data set, or\n",
+    "* a sequence of rows that each contain all information about a single individual in a data set.\n",
+    "\n",
+    "We will study dfs in great detail in the next several chapters. For now, we will just introduce a few methods without going into technical details. \n",
+    "\n",
+    "The df `cones` has been imported for us; later we will see how, but here we will just work with it. First, let's take a look at it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The DataFrame has six rows. Each row corresponds to one ice cream cone. The ice cream cones are the *individuals*.\n",
+    "\n",
+    "Each cone has three attributes: flavor, color, and price. Each column contains the data on one of these attributes, and so all the entries of any single column are of the same kind. Each column has a label. We will refer to columns by their labels.\n",
+    "\n",
+    "A df method is just like a function, but it must operate on a df. So the call looks like\n",
+    "\n",
+    "`name_of_DataFrame.method(arguments)`\n",
+    "\n",
+    "For example, if you want to see just the first two rows of a df, you can use the df method `head`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.head(2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can replace 2 by any number of rows. If you ask for more than six, you will only get six, because `cones` only has six rows."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Choosing Sets of Columns\n",
+    "The method `select` creates a new table consisting of only the specified columns.\n",
+    "We can state which columns we want to view by using dot '.' notation (not he same as in maths) or hard brackets with quotes. Note that an index is automatically generated, this is a fundamental aspect of the DataFrame as the index allows us to 'locate' members of the DataFrame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    strawberry\n",
+       "1     chocolate\n",
+       "2     chocolate\n",
+       "3    strawberry\n",
+       "4     chocolate\n",
+       "5     bubblegum\n",
+       "Name: Flavor, dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# single square brackets\n",
+    "\n",
+    "cones['Flavor']\n",
+    "\n",
+    "# uncomment (remove the hash mark) the line below to view the 'type()' of the output\n",
+    "\n",
+    "#type(cones['Flavor'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor\n",
+       "0  strawberry\n",
+       "1   chocolate\n",
+       "2   chocolate\n",
+       "3  strawberry\n",
+       "4   chocolate\n",
+       "5   bubblegum"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# double square brackets\n",
+    "\n",
+    "cones[['Flavor']]\n",
+    "\n",
+    "# uncomment the line below to view the 'type()' of the output\n",
+    "\n",
+    "# type(cones[['Flavor']])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    strawberry\n",
+       "1     chocolate\n",
+       "2     chocolate\n",
+       "3    strawberry\n",
+       "4     chocolate\n",
+       "5     bubblegum\n",
+       "Name: Flavor, dtype: object"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.Flavor"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This leaves the original table unchanged."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25\n",
+       "5   bubblegum         pink   4.75"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can select more than one column, by separating the column labels by commas. When you wish to view more than one column the 'hard brackets' must be used twice."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   5.25\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25\n",
+       "5   bubblegum   4.75"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[['Flavor', 'Price']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can also *drop* columns you don't want. The table above can be created by dropping the `Color` column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   5.25\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25\n",
+       "5   bubblegum   4.75"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.drop(columns=['Color'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can name this new table and look at it again by just typing its name."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   5.25\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25\n",
+       "5   bubblegum   4.75"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "no_colors = cones.drop(columns=['Color'])\n",
+    "\n",
+    "no_colors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Like selecting columns using hard brackets or dot notation, the `drop` method creates a smaller table and leaves the original table unchanged. In order to explore your data, you can create any number of smaller tables by using choosing or dropping columns. It will do no harm to your original data table."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Sorting Rows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `sort_values` method creates a new table by arranging the rows of the original table in ascending order of the values in the specified column. Here the `cones` table has been sorted in ascending order of the price of the cones.\n",
+    "\n",
+    "[pandas sort_values](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sort_values.html#pandas-dataframe-sort-values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "0  strawberry         pink   3.55\n",
+       "1   chocolate  light brown   4.75\n",
+       "5   bubblegum         pink   4.75\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.sort_values('Price')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To sort in descending order, you can use an *optional* argument to `sort`. As the name implies, optional arguments don't have to be used, but they can be used if you want to change the default behavior of a method. \n",
+    "\n",
+    "By default, `sort` sorts in increasing order of the values in the specified column. To sort in decreasing order, use the optional argument `ascending=False`, the default value for `ascending` is `True`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>bubblegum</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>pink</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor        Color  Price\n",
+       "2   chocolate   dark brown   5.25\n",
+       "3  strawberry         pink   5.25\n",
+       "4   chocolate   dark brown   5.25\n",
+       "1   chocolate  light brown   4.75\n",
+       "5   bubblegum         pink   4.75\n",
+       "0  strawberry         pink   3.55"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.sort_values('Price', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As when selecting and `drop`ing the `sort` method leaves the original table unchanged."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Selecting Rows that Satisfy a Condition\n",
+    "Creating a new DataFrame (in database world this wold be a 'view'), consisting only of the rows that satisfy a given condition we use the 'exactly equal to' `==`. In this section we will work with a very simple condition, which is that the value in a specified column must be exactly equal to a value that we also specify. Thus the `==` method has two arguments.\n",
+    "\n",
+    "The code in the cell below creates a df consisting only of the rows corresponding to chocolate cones."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>light brown</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>dark brown</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Flavor        Color  Price\n",
+       "1  chocolate  light brown   4.75\n",
+       "2  chocolate   dark brown   5.25\n",
+       "4  chocolate   dark brown   5.25"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor']=='chocolate']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The arguments are the label of the column and the value we are looking for in that column. The `==` method can also be used when the condition that the rows must satisfy is more complicated. In those situations the call will be a little more complicated as well.\n",
+    "\n",
+    "It is important to provide the value exactly. For example, if we specify `Chocolate` instead of `chocolate`, then `where` correctly finds no rows where the flavor is `Chocolate`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Color</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [Flavor, Color, Price]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor'] == 'Chocolate']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Like all the other table methods in this section, `==` leaves the original table unchanged."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example: Salaries in the NBA"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\"The NBA is the highest paying professional sports league in the world,\" [reported CNN](http://edition.cnn.com/2015/12/04/sport/gallery/highest-paid-nba-players/) in March 2016. The table `nba` contains the [salaries of all National Basketball Association players](https://www.statcrunch.com/app/index.php?dataid=1843341) in 2015-2016.\n",
+    "\n",
+    "Each row represents one player. The columns are:\n",
+    "\n",
+    "| **Column Label**   | Description                                         |\n",
+    "|--------------------|-----------------------------------------------------|\n",
+    "| `PLAYER`           | Player's name                                       |\n",
+    "| `POSITION`         | Player's position on team                           |\n",
+    "| `TEAM`             | Team name                                           |\n",
+    "|`SALARY`    | Player's salary in 2015-2016, in millions of dollars|\n",
+    " \n",
+    "The code for the positions is PG (Point Guard), SG (Shooting Guard), PF (Power Forward), SF (Small Forward), and C (Center). But what follows doesn't involve details about how basketball is played.\n",
+    "\n",
+    "The first row shows that Paul Millsap, Power Forward for the Atlanta Hawks, had a salary of almost $\\$18.7$ million in 2015-2016."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM     SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks  18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks  12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks   9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks   8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks   5.746479\n",
+       "..               ...      ...                 ...        ...\n",
+       "412        Gary Neal       PG  Washington Wizards   2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards   2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards   1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards   1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards   0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Fans of Stephen Curry can find his row by using `where`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            PLAYER POSITION                   TEAM     SALARY\n",
+       "121  Stephen Curry       PG  Golden State Warriors  11.370786"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['PLAYER'] == 'Stephen Curry']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also create a new table called `warriors` consisting of just the data for the Golden State Warriors."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "warriors = nba[nba['TEAM'] =='Golden State Warriors']\n",
+    "warriors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "By default, the first 10 lines of a table are displayed. You can use `head()` to display more or fewer. To display the entire table type the name of the DataFrame."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "warriors"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `nba` table is sorted in alphabetical order of the team names. To see how the players were paid in 2015-2016, it is useful to sort the data by salary. Remember that by default, the sorting is in increasing order."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>325</th>\n",
+       "      <td>Phil Pressey</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "325            Phil Pressey       PG         Phoenix Suns   0.055722\n",
+       "..                      ...      ...                  ...        ...\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These figures are somewhat difficult to compare as some of these players changed teams during the season and received salaries from more than one team; only the salary from the last team appears in the table.  \n",
+    "\n",
+    "The CNN report is about the other end of the salary scale – the players who are among the highest paid in the world. To identify these players we can sort in descending order of salary and look at the top few rows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>200</th>\n",
+       "      <td>Elliot Williams</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Memphis Grizzlies</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "..                      ...      ...                  ...        ...\n",
+       "200         Elliot Williams       SG    Memphis Grizzlies   0.055722\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Kobe Bryant, since retired, was the highest earning NBA player in 2015-2016."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

03/programming-in-python.md

@@ -0,0 +1,10 @@
+# 3. Programming in Python
+Programming can dramatically improve our ability to collect and analyze information
+about the world, which in turn can lead to discoveries through the kind of careful
+reasoning demonstrated in the previous section. In data science, the purpose of
+writing a program is to instruct a computer to carry out the steps of an analysis.
+Computers cannot study the world on their own. People must describe precisely what
+steps the computer should take in order to collect and analyze data, and those steps
+are expressed through programs.
+
+

04/1/.ipynb_checkpoints/Numbers-checkpoint.ipynb

@@ -0,0 +1,502 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Numbers\n",
+    "\n",
+    "Computers are designed to perform numerical calculations, but there are some important details about working with numbers that every programmer working with quantitative data should know. Python (and most other programming languages) distinguishes between two different types of numbers:\n",
+    "\n",
+    "* Integers are called `int` values in the Python language. They can only represent whole numbers (negative, zero, or positive) that don't have a fractional component\n",
+    "* Real numbers are called `float` values (or *floating point values*) in the Python language. They can represent whole or fractional numbers but have some limitations.\n",
+    "\n",
+    "The type of a number is evident from the way it is displayed: `int` values have no decimal point and `float` values always have a decimal point. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Some int values\n",
+    "2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 + 3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-1234567890000000000"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "-1234567890000000000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.2"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Some float values\n",
+    "1.2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3.0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When a `float` value is combined with an `int` value using some arithmetic operator, then the result is always a `float` value. In most cases, two integers combine to form another integer, but any number (`int` or `float`) divided by another will be a `float` value. Very large or very small `float` values are displayed using scientific notation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.5"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1.5 + 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 / 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-1.23456789e+19"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "-12345678900000000000.0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `type` function can be used to find the type of any number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "int"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "float"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(3 / 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `type` of an expression is the type of its final value. So, the `type` function will never indicate that the type of an expression is a name, because names are always evaluated to their assigned values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "int"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = 3\n",
+    "type(x) # The type of x is an int, not a name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "float"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(x + 2.5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## More About Float Values\n",
+    "\n",
+    "Float values are very flexible, but they do have limits. \n",
+    "\n",
+    "1. A `float` can represent extremely large and extremely small numbers. There are limits, but you will rarely encounter them.\n",
+    "2. A `float` only represents 15 or 16 significant digits for any number; the remaining precision is lost. This limited precision is enough for the vast majority of applications.\n",
+    "3. After combining `float` values with arithmetic, the last few digits may be incorrect. Small rounding errors are often confusing when first encountered.\n",
+    "\n",
+    "The first limit can be observed in two ways. If the result of a computation is a very large number, then it is represented as infinite. If the result is a very small number, then it is represented as zero."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2e+307"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e306 * 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "inf"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e306 * 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2e-323"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e-322 / 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e-322 / 100"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The second limit can be observed by an expression that involves numbers with more than 15 significant digits. These extra digits are discarded before any arithmetic is carried out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "0.6666666666666666 - 0.6666666666666666123456789"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The third limit can be observed when taking the difference between two expressions that should be equivalent. For example, the expression `2 ** 0.5` computes the square root of 2, but squaring this value does not exactly recover 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.4142135623730951"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2 ** 0.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2.0000000000000004"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(2 ** 0.5) * (2 ** 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.440892098500626e-16"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(2 ** 0.5) * (2 ** 0.5) - 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The final result above is `0.0000000000000004440892098500626`, a number that is very close to zero. The correct answer to this arithmetic expression is 0, but a small error in the final significant digit appears very different in scientific notation. This behavior appears in almost all programming languages because it is the result of the standard way that arithmetic is carried out on computers. \n",
+    "\n",
+    "Although `float` values are not always exact, they are certainly reliable and work the same way across all different kinds of computers and programming languages. "
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/1/Numbers.ipynb

@@ -0,0 +1,502 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Numbers\n",
+    "\n",
+    "Computers are designed to perform numerical calculations, but there are some important details about working with numbers that every programmer working with quantitative data should know. Python (and most other programming languages) distinguishes between two different types of numbers:\n",
+    "\n",
+    "* Integers are called `int` values in the Python language. They can only represent whole numbers (negative, zero, or positive) that don't have a fractional component\n",
+    "* Real numbers are called `float` values (or *floating point values*) in the Python language. They can represent whole or fractional numbers but have some limitations.\n",
+    "\n",
+    "The type of a number is evident from the way it is displayed: `int` values have no decimal point and `float` values always have a decimal point. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Some int values\n",
+    "2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 + 3"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-1234567890000000000"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "-1234567890000000000"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.2"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Some float values\n",
+    "1.2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3.0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When a `float` value is combined with an `int` value using some arithmetic operator, then the result is always a `float` value. In most cases, two integers combine to form another integer, but any number (`int` or `float`) divided by another will be a `float` value. Very large or very small `float` values are displayed using scientific notation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.5"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1.5 + 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.0"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 / 1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-1.23456789e+19"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "-12345678900000000000.0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `type` function can be used to find the type of any number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "int"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "float"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(3 / 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `type` of an expression is the type of its final value. So, the `type` function will never indicate that the type of an expression is a name, because names are always evaluated to their assigned values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "int"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = 3\n",
+    "type(x) # The type of x is an int, not a name"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "float"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(x + 2.5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## More About Float Values\n",
+    "\n",
+    "Float values are very flexible, but they do have limits. \n",
+    "\n",
+    "1. A `float` can represent extremely large and extremely small numbers. There are limits, but you will rarely encounter them.\n",
+    "2. A `float` only represents 15 or 16 significant digits for any number; the remaining precision is lost. This limited precision is enough for the vast majority of applications.\n",
+    "3. After combining `float` values with arithmetic, the last few digits may be incorrect. Small rounding errors are often confusing when first encountered.\n",
+    "\n",
+    "The first limit can be observed in two ways. If the result of a computation is a very large number, then it is represented as infinite. If the result is a very small number, then it is represented as zero."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2e+307"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e306 * 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "inf"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e306 * 100"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2e-323"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e-322 / 10"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2e-322 / 100"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The second limit can be observed by an expression that involves numbers with more than 15 significant digits. These extra digits are discarded before any arithmetic is carried out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.0"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "0.6666666666666666 - 0.6666666666666666123456789"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The third limit can be observed when taking the difference between two expressions that should be equivalent. For example, the expression `2 ** 0.5` computes the square root of 2, but squaring this value does not exactly recover 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1.4142135623730951"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2 ** 0.5"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2.0000000000000004"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(2 ** 0.5) * (2 ** 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4.440892098500626e-16"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(2 ** 0.5) * (2 ** 0.5) - 2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The final result above is `0.0000000000000004440892098500626`, a number that is very close to zero. The correct answer to this arithmetic expression is 0, but a small error in the final significant digit appears very different in scientific notation. This behavior appears in almost all programming languages because it is the result of the standard way that arithmetic is carried out on computers. \n",
+    "\n",
+    "Although `float` values are not always exact, they are certainly reliable and work the same way across all different kinds of computers and programming languages. "
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/2/.ipynb_checkpoints/Strings-checkpoint.ipynb

@@ -0,0 +1,145 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Strings\n",
+    "\n",
+    "Much of the world's data is text, and a piece of text represented in a computer is called a *string*. A string can represent a word, a sentence, or even the contents of every book in a library. Since text can include numbers (like this: 5) or truth values (True), a string can also describe those things.\n",
+    "\n",
+    "The meaning of an expression depends both upon its structure and the types of values that are being combined. So, for instance, adding two strings together produces another string. This expression is still an addition expression, but it is combining a different type of value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'datascience'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"data\" + \"science\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Addition is completely literal; it combines these two strings together without regard for their contents. It doesn't add a space because these are different words; that's up to the programmer (you) to specify."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'data science'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"data\" + \" \" + \"science\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Single and double quotes can both be used to create strings: `'hi'` and `\"hi\"` are identical expressions. Double quotes are often preferred because they allow you to include apostrophes inside of strings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"This won't work with a single-quoted string!\""
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"This won't work with a single-quoted string!\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Why not? Try it out."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `str` function returns a string representation of any value. Using this function, strings can be constructed that have embedded values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"That's 2 True\""
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"That's \" + str(1 + 1) + ' ' + str(True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/2/1/.ipynb_checkpoints/String_Methods-checkpoint.ipynb

@@ -0,0 +1,147 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# String Methods\n",
+    "\n",
+    "From an existing string, related strings can be constructed using string methods, which are functions that operate on strings. These methods are called by placing a dot after the string, then calling the function.\n",
+    "\n",
+    "For example, the following method generates an uppercased version of a string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'LOUD'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"loud\".upper()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Perhaps the most important method is `replace`, which replaces all instances of a substring within the string. The `replace` method takes two arguments, the text to be replaced and its replacement."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'matchmaker'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'hitchhiker'.replace('hi', 'ma')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "String methods can also be invoked using variable names, as long as those names are bound to strings. So, for instance, the following two-step process generates the word \"degrade\" starting from \"train\" by first creating \"ingrain\" and then applying a second replacement."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'degrade'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s = \"train\"\n",
+    "t = s.replace('t', 'ing')\n",
+    "u = t.replace('in', 'de')\n",
+    "u"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that the line `t = s.replace('t', 'ing')` doesn't change the string `s`, which is still \"train\".  The method call `s.replace('t', 'ing')` just has a value, which is the string \"ingrain\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'train'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the first time we've seen methods, but methods are not unique to strings.  As we will see shortly, other types of objects can have them."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/2/1/String_Methods.ipynb

@@ -0,0 +1,147 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# String Methods\n",
+    "\n",
+    "From an existing string, related strings can be constructed using string methods, which are functions that operate on strings. These methods are called by placing a dot after the string, then calling the function.\n",
+    "\n",
+    "For example, the following method generates an uppercased version of a string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'LOUD'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"loud\".upper()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Perhaps the most important method is `replace`, which replaces all instances of a substring within the string. The `replace` method takes two arguments, the text to be replaced and its replacement."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'matchmaker'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'hitchhiker'.replace('hi', 'ma')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "String methods can also be invoked using variable names, as long as those names are bound to strings. So, for instance, the following two-step process generates the word \"degrade\" starting from \"train\" by first creating \"ingrain\" and then applying a second replacement."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'degrade'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s = \"train\"\n",
+    "t = s.replace('t', 'ing')\n",
+    "u = t.replace('in', 'de')\n",
+    "u"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note that the line `t = s.replace('t', 'ing')` doesn't change the string `s`, which is still \"train\".  The method call `s.replace('t', 'ing')` just has a value, which is the string \"ingrain\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'train'"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is the first time we've seen methods, but methods are not unique to strings.  As we will see shortly, other types of objects can have them."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/2/Strings.ipynb

@@ -0,0 +1,145 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Strings\n",
+    "\n",
+    "Much of the world's data is text, and a piece of text represented in a computer is called a *string*. A string can represent a word, a sentence, or even the contents of every book in a library. Since text can include numbers (like this: 5) or truth values (True), a string can also describe those things.\n",
+    "\n",
+    "The meaning of an expression depends both upon its structure and the types of values that are being combined. So, for instance, adding two strings together produces another string. This expression is still an addition expression, but it is combining a different type of value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'datascience'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"data\" + \"science\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Addition is completely literal; it combines these two strings together without regard for their contents. It doesn't add a space because these are different words; that's up to the programmer (you) to specify."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'data science'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"data\" + \" \" + \"science\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Single and double quotes can both be used to create strings: `'hi'` and `\"hi\"` are identical expressions. Double quotes are often preferred because they allow you to include apostrophes inside of strings."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"This won't work with a single-quoted string!\""
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"This won't work with a single-quoted string!\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Why not? Try it out."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `str` function returns a string representation of any value. Using this function, strings can be constructed that have embedded values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"That's 2 True\""
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"That's \" + str(1 + 1) + ' ' + str(True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/3/.ipynb_checkpoints/Comparison-checkpoint.ipynb

@@ -0,0 +1,153 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Comparisons\n",
+    "\n",
+    "Boolean values most often arise from comparison operators. Python includes a variety of operators that compare values. For example, `3` is larger than `1 + 1`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 > 1 + 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The value `True` indicates that the comparison is valid; Python has confirmed this simple fact about the relationship between `3` and `1+1`. The full set of common comparison operators are listed below.\n",
+    "\n",
+    "| Comparison         | Operator | True example | False Example |\n",
+    "|--------------------|----------|--------------|---------------|\n",
+    "| Less than          | <        | 2 < 3        | 2 < 2         |\n",
+    "| Greater than       | >        | 3>2          | 3>3           |\n",
+    "| Less than or equal | <=       | 2 <= 2       | 3 <= 2        |\n",
+    "| Greater or equal   | >=       | 3 >= 3       | 2 >= 3        |\n",
+    "| Equal              | ==       | 3 == 3       | 3 == 2        |\n",
+    "| Not equal          | !=       | 3 != 2       | 2 != 2        |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An expression can contain multiple comparisons, and they all must hold in order for the whole expression to be `True`. For example, we can express that `1+1` is between `1` and `3` using the following expression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 < 1 + 1 < 3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The average of two numbers is always between the smaller number and the larger number. We express this relationship for the numbers `x` and `y` below. You can try different values of `x` and `y` to confirm this relationship."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = 12\n",
+    "y = 5\n",
+    "min(x, y) <= (x+y)/2 <= max(x, y)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Strings can also be compared, and their order is alphabetical. A shorter string is less than a longer string that begins with the shorter string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"Dog\" > \"Catastrophe\" > \"Cat\""
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/3/Comparison.ipynb

@@ -0,0 +1,153 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Comparisons\n",
+    "\n",
+    "Boolean values most often arise from comparison operators. Python includes a variety of operators that compare values. For example, `3` is larger than `1 + 1`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 > 1 + 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The value `True` indicates that the comparison is valid; Python has confirmed this simple fact about the relationship between `3` and `1+1`. The full set of common comparison operators are listed below.\n",
+    "\n",
+    "| Comparison         | Operator | True example | False Example |\n",
+    "|--------------------|----------|--------------|---------------|\n",
+    "| Less than          | <        | 2 < 3        | 2 < 2         |\n",
+    "| Greater than       | >        | 3>2          | 3>3           |\n",
+    "| Less than or equal | <=       | 2 <= 2       | 3 <= 2        |\n",
+    "| Greater or equal   | >=       | 3 >= 3       | 2 >= 3        |\n",
+    "| Equal              | ==       | 3 == 3       | 3 == 2        |\n",
+    "| Not equal          | !=       | 3 != 2       | 2 != 2        |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An expression can contain multiple comparisons, and they all must hold in order for the whole expression to be `True`. For example, we can express that `1+1` is between `1` and `3` using the following expression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 < 1 + 1 < 3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The average of two numbers is always between the smaller number and the larger number. We express this relationship for the numbers `x` and `y` below. You can try different values of `x` and `y` to confirm this relationship."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = 12\n",
+    "y = 5\n",
+    "min(x, y) <= (x+y)/2 <= max(x, y)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Strings can also be compared, and their order is alphabetical. A shorter string is less than a longer string that begins with the shorter string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"Dog\" > \"Catastrophe\" > \"Cat\""
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

04/Data_Types.ipynb

@@ -0,0 +1,58 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 4. Data Types\n",
+    "\n",
+    "Every value has a type, and the built-in `type` function returns the type of the result of any expression."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One type we have encountered already is a built-in function. Python indicates that the type is a `builtin_function_or_method`; the distinction between a *function* and a *method* is not important at this stage."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "type(abs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This chapter will explore many useful types of data."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/1/.ipynb_checkpoints/Arrays-checkpoint.ipynb

@@ -0,0 +1,304 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Arrays\n",
+    "\n",
+    "While there are many kinds of collections in Python, we will work primarily with arrays in this class. We've already seen that the `make_array` function can be used to create arrays of numbers.\n",
+    "\n",
+    "Arrays can also contain strings or other types of values, but a single array can only contain a single kind of data. (It usually doesn't make sense to group together unlike data anyway.)  For example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['noun', 'pronoun', 'verb', 'adverb', 'adjective', 'conjunction',\n",
+       "       'preposition', 'interjection'], dtype='<U12')"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "english_parts_of_speech = np.array([\"noun\", \"pronoun\", \"verb\", \"adverb\", \"adjective\", \"conjunction\", \"preposition\", \"interjection\"])\n",
+    "english_parts_of_speech"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Returning to the temperature data, we create arrays of average daily [high temperatures](http://berkeleyearth.lbl.gov/auto/Regional/TMAX/Text/global-land-TMAX-Trend.txt) for the decades surrounding 1850, 1900, 1950, and 2000."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([13.6  , 14.387, 14.585, 15.164])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_high = 14.48\n",
+    "highs = np.array([baseline_high - 0.880, \n",
+    "                   baseline_high - 0.093,\n",
+    "                   baseline_high + 0.105, \n",
+    "                   baseline_high + 0.684])\n",
+    "highs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Arrays can be used in arithmetic expressions to compute over their contents. When an array is combined with a single number, that number is combined with each element of the array. Therefore, we can convert all of these temperatures to Fahrenheit by writing the familiar conversion formula."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([56.48  , 57.8966, 58.253 , 59.2952])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(9/5) * highs + 32"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"array_arithmetic.png\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Arrays also have *methods*, which are functions that operate on the array values. The `mean` of a collection of numbers is its average value: the sum divided by the length. Each pair of parentheses in the examples below is part of a call expression; it's calling a function with no arguments to perform a computation on the array called `highs`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs.size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "57.736000000000004"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.434000000000001"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs.mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Functions on Arrays\n",
+    "The `numpy` package, abbreviated `np` in programs, provides Python programmers with convenient and powerful functions for creating and manipulating arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For example, the `diff` function computes the difference between each adjacent pair of elements in an array. The first element of the `diff` is the second element minus the first. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.787, 0.198, 0.579])"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.diff(highs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The [full Numpy reference](http://docs.scipy.org/doc/numpy/reference/) lists these functions exhaustively, but only a small subset are used commonly for data processing applications. These are grouped into different packages within `np`. Learning this vocabulary is an important part of learning the Python language, so refer back to this list often as you work through examples and problems.\n",
+    "\n",
+    "However, you **don't need to memorize these**.  Use this as a reference.\n",
+    "\n",
+    "Each of these functions takes an array as an argument and returns a single value.\n",
+    "\n",
+    "| **Function**       | Description                                                          |\n",
+    "|--------------------|----------------------------------------------------------------------|\n",
+    "| `np.prod`          | Multiply all elements together                                       |\n",
+    "| `np.sum`           | Add all elements together                                            |\n",
+    "| `np.all`           | Test whether all elements are true values (non-zero numbers are true)|\n",
+    "| `np.any`           | Test whether any elements are true values (non-zero numbers are true)|\n",
+    "| `np.count_nonzero` | Count the number of non-zero elements                                |\n",
+    "\n",
+    "Each of these functions takes an array as an argument and returns an array of values.\n",
+    "\n",
+    "| **Function**       | Description                                                          |\n",
+    "|--------------------|----------------------------------------------------------------------|\n",
+    "| `np.diff`          | Difference between adjacent elements                                 |\n",
+    "| `np.round`         | Round each number to the nearest integer (whole number)              |\n",
+    "| `np.cumprod`       | A cumulative product: for each element, multiply all elements so far |\n",
+    "| `np.cumsum`        | A cumulative sum: for each element, add all elements so far          |\n",
+    "| `np.exp`           | Exponentiate each element                                            |\n",
+    "| `np.log`           | Take the natural logarithm of each element                           |\n",
+    "| `np.sqrt`          | Take the square root of each element                                 |\n",
+    "| `np.sort`          | Sort the elements                                                    |\n",
+    "\n",
+    "Each of these functions takes an array of strings and returns an array.\n",
+    "\n",
+    "| **Function**        | **Description**                                              |\n",
+    "|---------------------|--------------------------------------------------------------|\n",
+    "| `np.char.lower`     | Lowercase each element                                       |\n",
+    "| `np.char.upper`     | Uppercase each element                                       |\n",
+    "| `np.char.strip`     | Remove spaces at the beginning or end of each element        |\n",
+    "| `np.char.isalpha`   | Whether each element is only letters (no numbers or symbols) |\n",
+    "| `np.char.isnumeric` | Whether each element is only numeric (no letters)  \n",
+    "\n",
+    "Each of these functions takes both an array of strings and a *search string*; each returns an array.\n",
+    "\n",
+    "| **Function**         | **Description**                                                                  |\n",
+    "|----------------------|----------------------------------------------------------------------------------|\n",
+    "| `np.char.count`      | Count the number of times a search string appears among the elements of an array |\n",
+    "| `np.char.find`       | The position within each element that a search string is found first             |\n",
+    "| `np.char.rfind`      | The position within each element that a search string is found last              |\n",
+    "| `np.char.startswith` | Whether each element starts with the search string  \n",
+    "\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/1/Arrays.ipynb

@@ -0,0 +1,304 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Arrays\n",
+    "\n",
+    "While there are many kinds of collections in Python, we will work primarily with arrays in this class. We've already seen that the `make_array` function can be used to create arrays of numbers.\n",
+    "\n",
+    "Arrays can also contain strings or other types of values, but a single array can only contain a single kind of data. (It usually doesn't make sense to group together unlike data anyway.)  For example:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['noun', 'pronoun', 'verb', 'adverb', 'adjective', 'conjunction',\n",
+       "       'preposition', 'interjection'], dtype='<U12')"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "english_parts_of_speech = np.array([\"noun\", \"pronoun\", \"verb\", \"adverb\", \"adjective\", \"conjunction\", \"preposition\", \"interjection\"])\n",
+    "english_parts_of_speech"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Returning to the temperature data, we create arrays of average daily [high temperatures](http://berkeleyearth.lbl.gov/auto/Regional/TMAX/Text/global-land-TMAX-Trend.txt) for the decades surrounding 1850, 1900, 1950, and 2000."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([13.6  , 14.387, 14.585, 15.164])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_high = 14.48\n",
+    "highs = np.array([baseline_high - 0.880, \n",
+    "                   baseline_high - 0.093,\n",
+    "                   baseline_high + 0.105, \n",
+    "                   baseline_high + 0.684])\n",
+    "highs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Arrays can be used in arithmetic expressions to compute over their contents. When an array is combined with a single number, that number is combined with each element of the array. Therefore, we can convert all of these temperatures to Fahrenheit by writing the familiar conversion formula."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([56.48  , 57.8966, 58.253 , 59.2952])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(9/5) * highs + 32"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"array_arithmetic.png\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Arrays also have *methods*, which are functions that operate on the array values. The `mean` of a collection of numbers is its average value: the sum divided by the length. Each pair of parentheses in the examples below is part of a call expression; it's calling a function with no arguments to perform a computation on the array called `highs`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs.size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "57.736000000000004"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs.sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.434000000000001"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs.mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Functions on Arrays\n",
+    "The `numpy` package, abbreviated `np` in programs, provides Python programmers with convenient and powerful functions for creating and manipulating arrays."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "For example, the `diff` function computes the difference between each adjacent pair of elements in an array. The first element of the `diff` is the second element minus the first. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.787, 0.198, 0.579])"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.diff(highs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The [full Numpy reference](http://docs.scipy.org/doc/numpy/reference/) lists these functions exhaustively, but only a small subset are used commonly for data processing applications. These are grouped into different packages within `np`. Learning this vocabulary is an important part of learning the Python language, so refer back to this list often as you work through examples and problems.\n",
+    "\n",
+    "However, you **don't need to memorize these**.  Use this as a reference.\n",
+    "\n",
+    "Each of these functions takes an array as an argument and returns a single value.\n",
+    "\n",
+    "| **Function**       | Description                                                          |\n",
+    "|--------------------|----------------------------------------------------------------------|\n",
+    "| `np.prod`          | Multiply all elements together                                       |\n",
+    "| `np.sum`           | Add all elements together                                            |\n",
+    "| `np.all`           | Test whether all elements are true values (non-zero numbers are true)|\n",
+    "| `np.any`           | Test whether any elements are true values (non-zero numbers are true)|\n",
+    "| `np.count_nonzero` | Count the number of non-zero elements                                |\n",
+    "\n",
+    "Each of these functions takes an array as an argument and returns an array of values.\n",
+    "\n",
+    "| **Function**       | Description                                                          |\n",
+    "|--------------------|----------------------------------------------------------------------|\n",
+    "| `np.diff`          | Difference between adjacent elements                                 |\n",
+    "| `np.round`         | Round each number to the nearest integer (whole number)              |\n",
+    "| `np.cumprod`       | A cumulative product: for each element, multiply all elements so far |\n",
+    "| `np.cumsum`        | A cumulative sum: for each element, add all elements so far          |\n",
+    "| `np.exp`           | Exponentiate each element                                            |\n",
+    "| `np.log`           | Take the natural logarithm of each element                           |\n",
+    "| `np.sqrt`          | Take the square root of each element                                 |\n",
+    "| `np.sort`          | Sort the elements                                                    |\n",
+    "\n",
+    "Each of these functions takes an array of strings and returns an array.\n",
+    "\n",
+    "| **Function**        | **Description**                                              |\n",
+    "|---------------------|--------------------------------------------------------------|\n",
+    "| `np.char.lower`     | Lowercase each element                                       |\n",
+    "| `np.char.upper`     | Uppercase each element                                       |\n",
+    "| `np.char.strip`     | Remove spaces at the beginning or end of each element        |\n",
+    "| `np.char.isalpha`   | Whether each element is only letters (no numbers or symbols) |\n",
+    "| `np.char.isnumeric` | Whether each element is only numeric (no letters)  \n",
+    "\n",
+    "Each of these functions takes both an array of strings and a *search string*; each returns an array.\n",
+    "\n",
+    "| **Function**         | **Description**                                                                  |\n",
+    "|----------------------|----------------------------------------------------------------------------------|\n",
+    "| `np.char.count`      | Count the number of times a search string appears among the elements of an array |\n",
+    "| `np.char.find`       | The position within each element that a search string is found first             |\n",
+    "| `np.char.rfind`      | The position within each element that a search string is found last              |\n",
+    "| `np.char.startswith` | Whether each element starts with the search string  \n",
+    "\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/2/.ipynb_checkpoints/Ranges-checkpoint.ipynb

@@ -0,0 +1,333 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ranges\n",
+    "\n",
+    "A *range* is an array of numbers in increasing or decreasing order, each separated by a regular interval. \n",
+    "Ranges are useful in a surprisingly large number of situations, so it's worthwhile to learn about them.\n",
+    "\n",
+    "Ranges are defined  using the `np.arange` function, which takes either one, two, or three arguments: a start, and end, and a 'step'.\n",
+    "\n",
+    "If you pass one argument to `np.arange`, this becomes the `end` value, with `start=0`, `step=1` assumed.  Two arguments give the `start` and `end` with `step=1` assumed.  Three arguments give the `start`, `end` and `step` explicitly.\n",
+    "\n",
+    "A range always includes its `start` value, but does not include its `end` value.  It counts up by `step`, and it stops before it gets to the `end`.\n",
+    "\n",
+    "    np.arange(end): An array starting with 0 of increasing consecutive integers, stopping before end."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 1, 2, 3, 4])"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Notice how the array starts at 0 and goes only up to 4, not to the end value of 5."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "    np.arange(start, end): An array of consecutive increasing integers from start, stopping before end."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([3, 4, 5, 6, 7, 8])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(3, 9)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "    np.arange(start, end, step): A range with a difference of step between each pair of consecutive values, starting from start and stopping before end."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 3,  8, 13, 18, 23, 28])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(3, 30, 5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This array starts at 3, then takes a step of 5 to get to 8, then another step of 5 to get to 13, and so on.\n",
+    "\n",
+    "When you specify a step, the start, end, and step can all be either positive or negative and may be whole numbers or fractions. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1.5,  1. ,  0.5,  0. , -0.5, -1. , -1.5])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(1.5, -2, -0.5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example: Leibniz's formula for $\\pi$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The great German mathematician and philosopher [Gottfried Wilhelm Leibniz](https://en.wikipedia.org/wiki/Gottfried_Wilhelm_Leibniz) \n",
+    "(1646 - 1716) discovered a wonderful formula for $\\pi$ as an infinite sum of simple fractions. The formula is\n",
+    "\n",
+    "$$\\pi = 4 \\cdot \\left(1 - \\frac{1}{3} + \\frac{1}{5} - \\frac{1}{7} + \\frac{1}{9} - \\frac{1}{11} + \\dots\\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Though some math is needed to establish this, we can use arrays to convince ourselves that the formula works. Let's calculate the first 5000 terms of Leibniz's infinite sum and see if it is close to $\\pi$.\n",
+    "\n",
+    "$$4 \\cdot \\left(1 - \\frac{1}{3} + \\frac{1}{5} - \\frac{1}{7} + \\frac{1}{9} - \\frac{1}{11} + \\dots - \\frac{1}{9999} \\right)$$\n",
+    "\n",
+    "We will calculate this finite sum by adding all the positive terms first and then subtracting the sum of all the negative terms [[1]](#footnotes):\n",
+    "\n",
+    "$$4 \\cdot \\left( \\left(1 + \\frac{1}{5} + \\frac{1}{9} + \\dots + \\frac{1}{9997} \\right) - \\left(\\frac{1}{3} + \\frac{1}{7} + \\frac{1}{11} + \\dots + \\frac{1}{9999} \\right) \\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The positive terms in the sum have 1, 5, 9, and so on in the denominators. The array `by_four_to_20` contains these numbers up to 17:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1,  5,  9, 13, 17])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "by_four_to_20 = np.arange(1, 20, 4)\n",
+    "by_four_to_20"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To get an accurate approximation to $\\pi$, we'll use the much longer array `positive_term_denominators`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   1,    5,    9, ..., 9989, 9993, 9997])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "positive_term_denominators = np.arange(1, 10000, 4)\n",
+    "positive_term_denominators"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The positive terms we actually want to add together are just 1 over these denominators:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "positive_terms = 1 / positive_term_denominators"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The negative terms have 3, 7, 11, and so on on in their denominators. This array is just 2 added to `positive_term_denominators`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "negative_terms = 1 / (positive_term_denominators + 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The overall sum is"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.1413926535917955"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "4 * ( sum(positive_terms) - sum(negative_terms) )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is very close to $\\pi = 3.14159\\dots$. Leibniz's formula is looking good!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a id='footnotes'></a>\n",
+    "### Footnotes\n",
+    "[1] Surprisingly, when we add  *infinitely* many fractions, the order can matter! But our approximation to $\\pi$ uses only a large finite number of fractions, so it's okay to add the terms in any convenient order."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/2/Ranges.ipynb

@@ -0,0 +1,333 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ranges\n",
+    "\n",
+    "A *range* is an array of numbers in increasing or decreasing order, each separated by a regular interval. \n",
+    "Ranges are useful in a surprisingly large number of situations, so it's worthwhile to learn about them.\n",
+    "\n",
+    "Ranges are defined  using the `np.arange` function, which takes either one, two, or three arguments: a start, and end, and a 'step'.\n",
+    "\n",
+    "If you pass one argument to `np.arange`, this becomes the `end` value, with `start=0`, `step=1` assumed.  Two arguments give the `start` and `end` with `step=1` assumed.  Three arguments give the `start`, `end` and `step` explicitly.\n",
+    "\n",
+    "A range always includes its `start` value, but does not include its `end` value.  It counts up by `step`, and it stops before it gets to the `end`.\n",
+    "\n",
+    "    np.arange(end): An array starting with 0 of increasing consecutive integers, stopping before end."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 1, 2, 3, 4])"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Notice how the array starts at 0 and goes only up to 4, not to the end value of 5."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "    np.arange(start, end): An array of consecutive increasing integers from start, stopping before end."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([3, 4, 5, 6, 7, 8])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(3, 9)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "    np.arange(start, end, step): A range with a difference of step between each pair of consecutive values, starting from start and stopping before end."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 3,  8, 13, 18, 23, 28])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(3, 30, 5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This array starts at 3, then takes a step of 5 to get to 8, then another step of 5 to get to 13, and so on.\n",
+    "\n",
+    "When you specify a step, the start, end, and step can all be either positive or negative and may be whole numbers or fractions. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1.5,  1. ,  0.5,  0. , -0.5, -1. , -1.5])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.arange(1.5, -2, -0.5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example: Leibniz's formula for $\\pi$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The great German mathematician and philosopher [Gottfried Wilhelm Leibniz](https://en.wikipedia.org/wiki/Gottfried_Wilhelm_Leibniz) \n",
+    "(1646 - 1716) discovered a wonderful formula for $\\pi$ as an infinite sum of simple fractions. The formula is\n",
+    "\n",
+    "$$\\pi = 4 \\cdot \\left(1 - \\frac{1}{3} + \\frac{1}{5} - \\frac{1}{7} + \\frac{1}{9} - \\frac{1}{11} + \\dots\\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Though some math is needed to establish this, we can use arrays to convince ourselves that the formula works. Let's calculate the first 5000 terms of Leibniz's infinite sum and see if it is close to $\\pi$.\n",
+    "\n",
+    "$$4 \\cdot \\left(1 - \\frac{1}{3} + \\frac{1}{5} - \\frac{1}{7} + \\frac{1}{9} - \\frac{1}{11} + \\dots - \\frac{1}{9999} \\right)$$\n",
+    "\n",
+    "We will calculate this finite sum by adding all the positive terms first and then subtracting the sum of all the negative terms [[1]](#footnotes):\n",
+    "\n",
+    "$$4 \\cdot \\left( \\left(1 + \\frac{1}{5} + \\frac{1}{9} + \\dots + \\frac{1}{9997} \\right) - \\left(\\frac{1}{3} + \\frac{1}{7} + \\frac{1}{11} + \\dots + \\frac{1}{9999} \\right) \\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The positive terms in the sum have 1, 5, 9, and so on in the denominators. The array `by_four_to_20` contains these numbers up to 17:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 1,  5,  9, 13, 17])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "by_four_to_20 = np.arange(1, 20, 4)\n",
+    "by_four_to_20"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To get an accurate approximation to $\\pi$, we'll use the much longer array `positive_term_denominators`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([   1,    5,    9, ..., 9989, 9993, 9997])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "positive_term_denominators = np.arange(1, 10000, 4)\n",
+    "positive_term_denominators"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The positive terms we actually want to add together are just 1 over these denominators:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "positive_terms = 1 / positive_term_denominators"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The negative terms have 3, 7, 11, and so on on in their denominators. This array is just 2 added to `positive_term_denominators`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "negative_terms = 1 / (positive_term_denominators + 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The overall sum is"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.1413926535917955"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "4 * ( sum(positive_terms) - sum(negative_terms) )"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is very close to $\\pi = 3.14159\\dots$. Leibniz's formula is looking good!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a id='footnotes'></a>\n",
+    "### Footnotes\n",
+    "[1] Surprisingly, when we add  *infinitely* many fractions, the order can matter! But our approximation to $\\pi$ uses only a large finite number of fractions, so it's okay to add the terms in any convenient order."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/3/.ipynb_checkpoints/More_on_Arrays-checkpoint.ipynb

@@ -0,0 +1,278 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "path_images = '../../images/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# More on Arrays\n",
+    "It's often necessary to compute something that involves data from more than one array. If two arrays are of the same size, Python makes it easy to do calculations involving both arrays.\n",
+    "\n",
+    "For our first example, we return once more to the temperature data.  This time, we create arrays of average daily [high](http://berkeleyearth.lbl.gov/auto/Regional/TMAX/Text/global-land-TMAX-Trend.txt) and [low](http://berkeleyearth.lbl.gov/auto/Regional/TMIN/Text/global-land-TMIN-Trend.txt) temperatures for the decades surrounding 1850, 1900, 1950, and 2000."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([13.6  , 14.387, 14.585, 15.164])"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_high = 14.48\n",
+    "highs = np.array([baseline_high - 0.880, \n",
+    "                   baseline_high - 0.093,\n",
+    "                   baseline_high + 0.105, \n",
+    "                   baseline_high + 0.684])\n",
+    "highs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([2.128, 2.371, 2.874, 3.728])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_low = 3.00\n",
+    "lows = np.array([baseline_low - 0.872, baseline_low - 0.629,\n",
+    "                  baseline_low - 0.126, baseline_low + 0.728])\n",
+    "lows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Suppose we'd like to compute the average daily *range* of temperatures for each decade.  That is, we want to subtract the average daily high in the 1850s from the average daily low in the 1850s, and the same for each other decade.\n",
+    "\n",
+    "We could write this laboriously using `.item`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([11.472, 12.016, 11.711, 11.436])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# note - though the '.item()' can be used with numpy but not with pandas\n",
+    "# you can mix lines of pandas code with numpy code\n",
+    "\n",
+    "np.array(\n",
+    "    [highs.item(0) - lows.item(0),\n",
+    "    highs.item(1) - lows.item(1),\n",
+    "    highs.item(2) - lows.item(2),\n",
+    "    highs.item(3) - lows.item(3)]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As when we converted an array of temperatures from Celsius to Fahrenheit, Python provides a much cleaner way to write this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([11.472, 12.016, 11.711, 11.436])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs - lows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"array_subtraction.png\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What we've seen in these examples are special cases of a general feature of arrays."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Elementwise arithmetic on pairs of numerical arrays\n",
+    "If an arithmetic operator acts on two arrays of the same size, then the operation is performed on each corresponding pair of elements in the two arrays. The final result is an array. \n",
+    "\n",
+    "For example, if `array1` and `array2` have the same number of elements, then the value of `array1 * array2` is an array. Its first element is the first element of `array1` times the first element of `array2`, its second element is the second element of `array1` times the second element of `array2`, and so on."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example: Wallis' Formula for $\\pi$ \n",
+    "The number $\\pi$ is important in many different areas of math. Centuries before computers were invented, mathematicians worked on finding simple ways to approximate the numerical value of $\\pi$. We have already seen Leibniz's formula for $\\pi$. About half a century before Leibniz, the English mathematician [John Wallis](https://en.wikipedia.org/wiki/John_Wallis) (1616-1703) also expressed $\\pi$ in terms of simple fractions, as an infinite product.\n",
+    "\n",
+    "$$\n",
+    "\\pi = 2 \\cdot \\left( \\frac{2}{1}\\cdot\\frac{2}{3}\\cdot\\frac{4}{3}\\cdot\\frac{4}{5}\\cdot\\frac{6}{5}\\cdot\\frac{6}{7}\\dots \\right)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a product of \"even/odd\" fractions. Let's use arrays to multiply a million of them, and see if the product is close to $\\pi$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Remember that multiplication can done in any order [[1]](#footnotes), so we can readjust our calculation to:\n",
+    "\n",
+    "$$\\pi \\approx 2 \\cdot \\left( \\frac{2}{1} \\cdot \\frac{4}{3} \\cdot \\frac{6}{5} \\cdots \\frac{1,000,000}{999999} \\right) \\cdot \\left( \\frac{2}{3} \\cdot \\frac{4}{5} \\cdot \\frac{6}{7} \\cdots \\frac{1,000,000}{1,000,001} \\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We're now ready to do the calculation. We start by creating an array of even numbers 2, 4, 6, and so on upto 1,000,000. Then we create two lists of odd numbers: 1, 3, 5, 7, ... upto 999,999, and 3, 5, 7, ... upto 1,000,001."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "even = np.arange(2, 1000001, 2)\n",
+    "one_below_even = even - 1\n",
+    "one_above_even = even + 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Remember that `np.prod` multiplies all the elements of an array together. Now we can calculate Wallis' product, to a good approximation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.1415910827951143"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2 * np.prod(even/one_below_even) * np.prod(even/one_above_even)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That's $\\pi$ correct to five decimal places.  Wallis clearly came up with a great formula."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a id='footnotes'></a>\n",
+    "### Footnotes\n",
+    "[1] As we saw in the example about Leibniz's formula, when we add  *infinitely* many fractions, the order can matter. The same is true with multiplying fractions, as we are doing here. But our approximation to $\\pi$ uses only a large finite number of fractions, so it's okay to multiply the terms in any convenient order."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/3/More_on_Arrays.ipynb

@@ -0,0 +1,278 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "path_images = '../../images/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# More on Arrays\n",
+    "It's often necessary to compute something that involves data from more than one array. If two arrays are of the same size, Python makes it easy to do calculations involving both arrays.\n",
+    "\n",
+    "For our first example, we return once more to the temperature data.  This time, we create arrays of average daily [high](http://berkeleyearth.lbl.gov/auto/Regional/TMAX/Text/global-land-TMAX-Trend.txt) and [low](http://berkeleyearth.lbl.gov/auto/Regional/TMIN/Text/global-land-TMIN-Trend.txt) temperatures for the decades surrounding 1850, 1900, 1950, and 2000."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([13.6  , 14.387, 14.585, 15.164])"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_high = 14.48\n",
+    "highs = np.array([baseline_high - 0.880, \n",
+    "                   baseline_high - 0.093,\n",
+    "                   baseline_high + 0.105, \n",
+    "                   baseline_high + 0.684])\n",
+    "highs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([2.128, 2.371, 2.874, 3.728])"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_low = 3.00\n",
+    "lows = np.array([baseline_low - 0.872, baseline_low - 0.629,\n",
+    "                  baseline_low - 0.126, baseline_low + 0.728])\n",
+    "lows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Suppose we'd like to compute the average daily *range* of temperatures for each decade.  That is, we want to subtract the average daily high in the 1850s from the average daily low in the 1850s, and the same for each other decade.\n",
+    "\n",
+    "We could write this laboriously using `.item`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([11.472, 12.016, 11.711, 11.436])"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# note - though the '.item()' can be used with numpy but not with pandas\n",
+    "# you can mix lines of pandas code with numpy code\n",
+    "\n",
+    "np.array(\n",
+    "    [highs.item(0) - lows.item(0),\n",
+    "    highs.item(1) - lows.item(1),\n",
+    "    highs.item(2) - lows.item(2),\n",
+    "    highs.item(3) - lows.item(3)]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As when we converted an array of temperatures from Celsius to Fahrenheit, Python provides a much cleaner way to write this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([11.472, 12.016, 11.711, 11.436])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "highs - lows"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<img src=\"array_subtraction.png\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What we've seen in these examples are special cases of a general feature of arrays."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Elementwise arithmetic on pairs of numerical arrays\n",
+    "If an arithmetic operator acts on two arrays of the same size, then the operation is performed on each corresponding pair of elements in the two arrays. The final result is an array. \n",
+    "\n",
+    "For example, if `array1` and `array2` have the same number of elements, then the value of `array1 * array2` is an array. Its first element is the first element of `array1` times the first element of `array2`, its second element is the second element of `array1` times the second element of `array2`, and so on."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Example: Wallis' Formula for $\\pi$ \n",
+    "The number $\\pi$ is important in many different areas of math. Centuries before computers were invented, mathematicians worked on finding simple ways to approximate the numerical value of $\\pi$. We have already seen Leibniz's formula for $\\pi$. About half a century before Leibniz, the English mathematician [John Wallis](https://en.wikipedia.org/wiki/John_Wallis) (1616-1703) also expressed $\\pi$ in terms of simple fractions, as an infinite product.\n",
+    "\n",
+    "$$\n",
+    "\\pi = 2 \\cdot \\left( \\frac{2}{1}\\cdot\\frac{2}{3}\\cdot\\frac{4}{3}\\cdot\\frac{4}{5}\\cdot\\frac{6}{5}\\cdot\\frac{6}{7}\\dots \\right)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a product of \"even/odd\" fractions. Let's use arrays to multiply a million of them, and see if the product is close to $\\pi$."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Remember that multiplication can done in any order [[1]](#footnotes), so we can readjust our calculation to:\n",
+    "\n",
+    "$$\\pi \\approx 2 \\cdot \\left( \\frac{2}{1} \\cdot \\frac{4}{3} \\cdot \\frac{6}{5} \\cdots \\frac{1,000,000}{999999} \\right) \\cdot \\left( \\frac{2}{3} \\cdot \\frac{4}{5} \\cdot \\frac{6}{7} \\cdots \\frac{1,000,000}{1,000,001} \\right)$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We're now ready to do the calculation. We start by creating an array of even numbers 2, 4, 6, and so on upto 1,000,000. Then we create two lists of odd numbers: 1, 3, 5, 7, ... upto 999,999, and 3, 5, 7, ... upto 1,000,001."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "even = np.arange(2, 1000001, 2)\n",
+    "one_below_even = even - 1\n",
+    "one_above_even = even + 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Remember that `np.prod` multiplies all the elements of an array together. Now we can calculate Wallis' product, to a good approximation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3.1415910827951143"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "2 * np.prod(even/one_below_even) * np.prod(even/one_above_even)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "That's $\\pi$ correct to five decimal places.  Wallis clearly came up with a great formula."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<a id='footnotes'></a>\n",
+    "### Footnotes\n",
+    "[1] As we saw in the example about Leibniz's formula, when we add  *infinitely* many fractions, the order can matter. The same is true with multiplying fractions, as we are doing here. But our approximation to $\\pi$ uses only a large finite number of fractions, so it's okay to multiply the terms in any convenient order."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

05/Sequences.ipynb

@@ -0,0 +1,134 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true,
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 5. Sequences"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Values can be grouped together into collections, which allows programmers to organize those values and refer to all of them with a single name. By grouping values together, we can write code that performs a computation on many pieces of data at once.\n",
+    "\n",
+    "Calling the function `np.array` on several values places them into an *array*, which is a kind of sequential collection. Below, we collect four different temperatures into an array called `highs`. These are the [estimated average daily high temperatures](http://berkeleyearth.lbl.gov/regions/global-land) over all land on Earth (in degrees Celsius) for the decades surrounding 1850, 1900, 1950, and 2000, respectively, expressed as deviations from the average absolute high temperature between 1951 and 1980, which was 14.48 degrees."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([13.6  , 14.387, 14.585, 15.164])"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "baseline_high = 14.48\n",
+    "highs = np.array([baseline_high - 0.880, baseline_high - 0.093,\n",
+    "                   baseline_high + 0.105, baseline_high + 0.684])\n",
+    "highs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Collections allow us to pass multiple values into a function using a single name. For instance, the `sum` function computes the sum of all values in a collection, and the `len` function computes its length. (That's the number of values we put in it.) Using them together, we can compute the average of a collection."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "14.434000000000001"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sum(highs)/len(highs)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The complete chart of daily high and low temperatures appears below. \n",
+    "\n",
+    "## Mean of Daily High Temperature\n",
+    "\n",
+    "![Mean of Daily High Temperature](http://berkeleyearth.lbl.gov/auto/Regional/TMAX/Figures/global-land-TMAX-Trend.png)\n",
+    "\n",
+    "## Mean of Daily Low Temperature\n",
+    "\n",
+    "![Mean of Daily Low Temperature](http://berkeleyearth.lbl.gov/auto/Regional/TMIN/Figures/global-land-TMIN-Trend.png)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/1/.ipynb_checkpoints/Sorting_Rows-checkpoint.ipynb

@@ -0,0 +1,870 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Sorting Rows\n",
+    "\n",
+    "\"The NBA is the highest paying professional sports league in the world,\" [reported CNN](http://edition.cnn.com/2015/12/04/sport/gallery/highest-paid-nba-players/) in March 2016. The table `nba_salaries` contains the salaries of all National Basketball Association players in 2015-2016.\n",
+    "\n",
+    "Each row represents one player. The columns are:\n",
+    "\n",
+    "| **Column Label**   | Description                                         |\n",
+    "|--------------------|-----------------------------------------------------|\n",
+    "| `PLAYER`           | Player's name                                       |\n",
+    "| `POSITION`         | Player's position on team                           |\n",
+    "| `TEAM`             | Team name                                           |\n",
+    "|`'15-'16 SALARY`    | Player's salary in 2015-2016, in millions of dollars|\n",
+    " \n",
+    "The code for the positions is PG (Point Guard), SG (Shooting Guard), PF (Power Forward), SF (Small Forward), and C (Center). But what follows doesn't involve details about how basketball is played.\n",
+    "\n",
+    "The first row shows that Paul Millsap, Power Forward for the Atlanta Hawks, had a salary of almost $\\$18.7$ million in 2015-2016."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>'15-'16 SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM  '15-'16 SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks       18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks       12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks        9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks        8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks        5.746479\n",
+       "..               ...      ...                 ...             ...\n",
+       "412        Gary Neal       PG  Washington Wizards        2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards        2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards        1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards        1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards        0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# This table can be found online: https://www.statcrunch.com/app/index.php?dataid=1843341\n",
+    "nba_salaries = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "nba_salaries"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The table contains 417 rows, one for each player. Only 10 of the rows are displayed. The `show` method allows us to specify the number of rows, with the default (no specification) being all the rows of the table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>'15-'16 SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           PLAYER POSITION           TEAM  '15-'16 SALARY\n",
+       "0    Paul Millsap       PF  Atlanta Hawks       18.671659\n",
+       "1      Al Horford        C  Atlanta Hawks       12.000000\n",
+       "2  Tiago Splitter        C  Atlanta Hawks        9.756250"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba_salaries.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Glance through about 20 rows or so, and you will see that the rows are in alphabetical order by team name. It's also possible to list the same rows in alphabetical order by player name using the `sort` method. The argument to `sort` is a column label or index."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>'15-'16 SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>68</th>\n",
+       "      <td>Aaron Brooks</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Chicago Bulls</td>\n",
+       "      <td>2.250000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>291</th>\n",
+       "      <td>Aaron Gordon</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Orlando Magic</td>\n",
+       "      <td>4.171680</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>Aaron Harrison</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Charlotte Hornets</td>\n",
+       "      <td>0.525093</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>235</th>\n",
+       "      <td>Adreian Payne</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Minnesota Timberwolves</td>\n",
+       "      <td>1.938840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             PLAYER POSITION                    TEAM  '15-'16 SALARY\n",
+       "68     Aaron Brooks       PG           Chicago Bulls        2.250000\n",
+       "291    Aaron Gordon       PF           Orlando Magic        4.171680\n",
+       "59   Aaron Harrison       SG       Charlotte Hornets        0.525093\n",
+       "235   Adreian Payne       PF  Minnesota Timberwolves        1.938840\n",
+       "1        Al Horford        C           Atlanta Hawks       12.000000"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba_salaries.sort_values('PLAYER').head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To examine the players' salaries, it would be much more helpful if the data were ordered by salary.\n",
+    "\n",
+    "To do this, we will first simplify the label of the column of salaries (just for convenience), and then sort by the new label `SALARY`. \n",
+    "\n",
+    "This arranges all the rows of the table in *increasing* order of salary, with the lowest salary appearing first. The output is a new table with the same columns as the original but with the rows rearranged."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>325</th>\n",
+       "      <td>Phil Pressey</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "325            Phil Pressey       PG         Phoenix Suns   0.055722\n",
+       "..                      ...      ...                  ...        ...\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba = nba_salaries.rename(columns={\"'15-'16 SALARY\": 'SALARY'})\n",
+    "nba.sort_values('SALARY')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These figures are somewhat difficult to compare as some of these players changed teams during the season and received salaries from more than one team; only the salary from the last team appears in the table. Point Guard Phil Pressey, for example, moved from Philadelphia to Phoenix during the year, and might be moving yet again to the Golden State Warriors. \n",
+    "\n",
+    "The CNN report is about the other end of the salary scale – the players who are among the highest paid in the world. \n",
+    "\n",
+    "To order the rows of the table in *decreasing* order of salary, we must use `sort` with the option `ascending=False`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>200</th>\n",
+       "      <td>Elliot Williams</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Memphis Grizzlies</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "..                      ...      ...                  ...        ...\n",
+       "200         Elliot Williams       SG    Memphis Grizzlies   0.055722\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Kobe Bryant, in his final season with the Lakers, was the highest paid at a salary of $\\$25$ million. Notice that the MVP Stephen Curry doesn't appear among the top 10. He is quite a bit further down the list, as we will see later."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Named Arguments\n",
+    "\n",
+    "The `descending=True` portion of this call expression is called a *named argument*. When a function or method is called, each argument has both a position and a name. Both are evident from the help text of a function or method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on method sort_values in module pandas.core.frame:\n",
+      "\n",
+      "sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, key: Union[Callable[[ForwardRef('Series')], Union[ForwardRef('Series'), ~AnyArrayLike]], NoneType] = None) method of pandas.core.frame.DataFrame instance\n",
+      "    Sort by the values along either axis.\n",
+      "    \n",
+      "    Parameters\n",
+      "    ----------\n",
+      "            by : str or list of str\n",
+      "                Name or list of names to sort by.\n",
+      "    \n",
+      "                - if `axis` is 0 or `'index'` then `by` may contain index\n",
+      "                  levels and/or column labels.\n",
+      "                - if `axis` is 1 or `'columns'` then `by` may contain column\n",
+      "                  levels and/or index labels.\n",
+      "    \n",
+      "                .. versionchanged:: 0.23.0\n",
+      "    \n",
+      "                   Allow specifying index or column level names.\n",
+      "    axis : {0 or 'index', 1 or 'columns'}, default 0\n",
+      "         Axis to be sorted.\n",
+      "    ascending : bool or list of bool, default True\n",
+      "         Sort ascending vs. descending. Specify list for multiple sort\n",
+      "         orders.  If this is a list of bools, must match the length of\n",
+      "         the by.\n",
+      "    inplace : bool, default False\n",
+      "         If True, perform operation in-place.\n",
+      "    kind : {'quicksort', 'mergesort', 'heapsort'}, default 'quicksort'\n",
+      "         Choice of sorting algorithm. See also ndarray.np.sort for more\n",
+      "         information.  `mergesort` is the only stable algorithm. For\n",
+      "         DataFrames, this option is only applied when sorting on a single\n",
+      "         column or label.\n",
+      "    na_position : {'first', 'last'}, default 'last'\n",
+      "         Puts NaNs at the beginning if `first`; `last` puts NaNs at the\n",
+      "         end.\n",
+      "    ignore_index : bool, default False\n",
+      "         If True, the resulting axis will be labeled 0, 1, …, n - 1.\n",
+      "    \n",
+      "         .. versionadded:: 1.0.0\n",
+      "    \n",
+      "    key : callable, optional\n",
+      "        Apply the key function to the values\n",
+      "        before sorting. This is similar to the `key` argument in the\n",
+      "        builtin :meth:`sorted` function, with the notable difference that\n",
+      "        this `key` function should be *vectorized*. It should expect a\n",
+      "        ``Series`` and return a Series with the same shape as the input.\n",
+      "        It will be applied to each column in `by` independently.\n",
+      "    \n",
+      "        .. versionadded:: 1.1.0\n",
+      "    \n",
+      "    Returns\n",
+      "    -------\n",
+      "    DataFrame or None\n",
+      "        DataFrame with sorted values if inplace=False, None otherwise.\n",
+      "    \n",
+      "    See Also\n",
+      "    --------\n",
+      "    DataFrame.sort_index : Sort a DataFrame by the index.\n",
+      "    Series.sort_values : Similar method for a Series.\n",
+      "    \n",
+      "    Examples\n",
+      "    --------\n",
+      "    >>> df = pd.DataFrame({\n",
+      "    ...     'col1': ['A', 'A', 'B', np.nan, 'D', 'C'],\n",
+      "    ...     'col2': [2, 1, 9, 8, 7, 4],\n",
+      "    ...     'col3': [0, 1, 9, 4, 2, 3],\n",
+      "    ...     'col4': ['a', 'B', 'c', 'D', 'e', 'F']\n",
+      "    ... })\n",
+      "    >>> df\n",
+      "      col1  col2  col3 col4\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    2    B     9     9    c\n",
+      "    3  NaN     8     4    D\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "    \n",
+      "    Sort by col1\n",
+      "    \n",
+      "    >>> df.sort_values(by=['col1'])\n",
+      "      col1  col2  col3 col4\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    2    B     9     9    c\n",
+      "    5    C     4     3    F\n",
+      "    4    D     7     2    e\n",
+      "    3  NaN     8     4    D\n",
+      "    \n",
+      "    Sort by multiple columns\n",
+      "    \n",
+      "    >>> df.sort_values(by=['col1', 'col2'])\n",
+      "      col1  col2  col3 col4\n",
+      "    1    A     1     1    B\n",
+      "    0    A     2     0    a\n",
+      "    2    B     9     9    c\n",
+      "    5    C     4     3    F\n",
+      "    4    D     7     2    e\n",
+      "    3  NaN     8     4    D\n",
+      "    \n",
+      "    Sort Descending\n",
+      "    \n",
+      "    >>> df.sort_values(by='col1', ascending=False)\n",
+      "      col1  col2  col3 col4\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "    2    B     9     9    c\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    3  NaN     8     4    D\n",
+      "    \n",
+      "    Putting NAs first\n",
+      "    \n",
+      "    >>> df.sort_values(by='col1', ascending=False, na_position='first')\n",
+      "      col1  col2  col3 col4\n",
+      "    3  NaN     8     4    D\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "    2    B     9     9    c\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    \n",
+      "    Sorting with a key function\n",
+      "    \n",
+      "    >>> df.sort_values(by='col4', key=lambda col: col.str.lower())\n",
+      "       col1  col2  col3 col4\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    2    B     9     9    c\n",
+      "    3  NaN     8     4    D\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "help(nba.sort_values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "At the very top of this `help` text, the *signature* of the `sort_value` method appears:\n",
+    "\n",
+    "    sort_value(column_or_label, descending=False, distinct=False)\n",
+    "    \n",
+    "This describes the positions, names, and default values of the three arguments to `sort_value`. When calling this method, you can use either positional arguments or named arguments, so the following three calls do exactly the same thing.\n",
+    "\n",
+    "    sort_value('SALARY', True)\n",
+    "    sort_value('SALARY', ascending=False)\n",
+    "    sort_value(column_or_label='SALARY', ascending=False)\n",
+    "    \n",
+    "When an argument is simply `True` or `False`, it's a useful convention to include the argument name so that it's more obvious what the argument value means."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/1/Sorting_Rows.ipynb

@@ -0,0 +1,870 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Sorting Rows\n",
+    "\n",
+    "\"The NBA is the highest paying professional sports league in the world,\" [reported CNN](http://edition.cnn.com/2015/12/04/sport/gallery/highest-paid-nba-players/) in March 2016. The table `nba_salaries` contains the salaries of all National Basketball Association players in 2015-2016.\n",
+    "\n",
+    "Each row represents one player. The columns are:\n",
+    "\n",
+    "| **Column Label**   | Description                                         |\n",
+    "|--------------------|-----------------------------------------------------|\n",
+    "| `PLAYER`           | Player's name                                       |\n",
+    "| `POSITION`         | Player's position on team                           |\n",
+    "| `TEAM`             | Team name                                           |\n",
+    "|`'15-'16 SALARY`    | Player's salary in 2015-2016, in millions of dollars|\n",
+    " \n",
+    "The code for the positions is PG (Point Guard), SG (Shooting Guard), PF (Power Forward), SF (Small Forward), and C (Center). But what follows doesn't involve details about how basketball is played.\n",
+    "\n",
+    "The first row shows that Paul Millsap, Power Forward for the Atlanta Hawks, had a salary of almost $\\$18.7$ million in 2015-2016."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>'15-'16 SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM  '15-'16 SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks       18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks       12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks        9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks        8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks        5.746479\n",
+       "..               ...      ...                 ...             ...\n",
+       "412        Gary Neal       PG  Washington Wizards        2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards        2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards        1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards        1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards        0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# This table can be found online: https://www.statcrunch.com/app/index.php?dataid=1843341\n",
+    "nba_salaries = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "nba_salaries"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The table contains 417 rows, one for each player. Only 10 of the rows are displayed. The `show` method allows us to specify the number of rows, with the default (no specification) being all the rows of the table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>'15-'16 SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           PLAYER POSITION           TEAM  '15-'16 SALARY\n",
+       "0    Paul Millsap       PF  Atlanta Hawks       18.671659\n",
+       "1      Al Horford        C  Atlanta Hawks       12.000000\n",
+       "2  Tiago Splitter        C  Atlanta Hawks        9.756250"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba_salaries.head(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Glance through about 20 rows or so, and you will see that the rows are in alphabetical order by team name. It's also possible to list the same rows in alphabetical order by player name using the `sort` method. The argument to `sort` is a column label or index."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>'15-'16 SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>68</th>\n",
+       "      <td>Aaron Brooks</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Chicago Bulls</td>\n",
+       "      <td>2.250000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>291</th>\n",
+       "      <td>Aaron Gordon</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Orlando Magic</td>\n",
+       "      <td>4.171680</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>59</th>\n",
+       "      <td>Aaron Harrison</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Charlotte Hornets</td>\n",
+       "      <td>0.525093</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>235</th>\n",
+       "      <td>Adreian Payne</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Minnesota Timberwolves</td>\n",
+       "      <td>1.938840</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             PLAYER POSITION                    TEAM  '15-'16 SALARY\n",
+       "68     Aaron Brooks       PG           Chicago Bulls        2.250000\n",
+       "291    Aaron Gordon       PF           Orlando Magic        4.171680\n",
+       "59   Aaron Harrison       SG       Charlotte Hornets        0.525093\n",
+       "235   Adreian Payne       PF  Minnesota Timberwolves        1.938840\n",
+       "1        Al Horford        C           Atlanta Hawks       12.000000"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba_salaries.sort_values('PLAYER').head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To examine the players' salaries, it would be much more helpful if the data were ordered by salary.\n",
+    "\n",
+    "To do this, we will first simplify the label of the column of salaries (just for convenience), and then sort by the new label `SALARY`. \n",
+    "\n",
+    "This arranges all the rows of the table in *increasing* order of salary, with the lowest salary appearing first. The output is a new table with the same columns as the original but with the rows rearranged."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>325</th>\n",
+       "      <td>Phil Pressey</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "325            Phil Pressey       PG         Phoenix Suns   0.055722\n",
+       "..                      ...      ...                  ...        ...\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba = nba_salaries.rename(columns={\"'15-'16 SALARY\": 'SALARY'})\n",
+    "nba.sort_values('SALARY')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These figures are somewhat difficult to compare as some of these players changed teams during the season and received salaries from more than one team; only the salary from the last team appears in the table. Point Guard Phil Pressey, for example, moved from Philadelphia to Phoenix during the year, and might be moving yet again to the Golden State Warriors. \n",
+    "\n",
+    "The CNN report is about the other end of the salary scale – the players who are among the highest paid in the world. \n",
+    "\n",
+    "To order the rows of the table in *decreasing* order of salary, we must use `sort` with the option `ascending=False`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>200</th>\n",
+       "      <td>Elliot Williams</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Memphis Grizzlies</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>324</th>\n",
+       "      <td>Orlando Johnson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.055722</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>327</th>\n",
+       "      <td>Cory Jefferson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>326</th>\n",
+       "      <td>Jordan McRae</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Phoenix Suns</td>\n",
+       "      <td>0.049709</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>267</th>\n",
+       "      <td>Thanasis Antetokounmpo</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>0.030888</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                     PLAYER POSITION                 TEAM     SALARY\n",
+       "169             Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "29              Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "72             LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "255         Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "131           Dwight Howard        C      Houston Rockets  22.359364\n",
+       "..                      ...      ...                  ...        ...\n",
+       "200         Elliot Williams       SG    Memphis Grizzlies   0.055722\n",
+       "324         Orlando Johnson       SG         Phoenix Suns   0.055722\n",
+       "327          Cory Jefferson       PF         Phoenix Suns   0.049709\n",
+       "326            Jordan McRae       SG         Phoenix Suns   0.049709\n",
+       "267  Thanasis Antetokounmpo       SF      New York Knicks   0.030888\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY', ascending=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Kobe Bryant, in his final season with the Lakers, was the highest paid at a salary of $\\$25$ million. Notice that the MVP Stephen Curry doesn't appear among the top 10. He is quite a bit further down the list, as we will see later."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Named Arguments\n",
+    "\n",
+    "The `descending=True` portion of this call expression is called a *named argument*. When a function or method is called, each argument has both a position and a name. Both are evident from the help text of a function or method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on method sort_values in module pandas.core.frame:\n",
+      "\n",
+      "sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last', ignore_index=False, key: Union[Callable[[ForwardRef('Series')], Union[ForwardRef('Series'), ~AnyArrayLike]], NoneType] = None) method of pandas.core.frame.DataFrame instance\n",
+      "    Sort by the values along either axis.\n",
+      "    \n",
+      "    Parameters\n",
+      "    ----------\n",
+      "            by : str or list of str\n",
+      "                Name or list of names to sort by.\n",
+      "    \n",
+      "                - if `axis` is 0 or `'index'` then `by` may contain index\n",
+      "                  levels and/or column labels.\n",
+      "                - if `axis` is 1 or `'columns'` then `by` may contain column\n",
+      "                  levels and/or index labels.\n",
+      "    \n",
+      "                .. versionchanged:: 0.23.0\n",
+      "    \n",
+      "                   Allow specifying index or column level names.\n",
+      "    axis : {0 or 'index', 1 or 'columns'}, default 0\n",
+      "         Axis to be sorted.\n",
+      "    ascending : bool or list of bool, default True\n",
+      "         Sort ascending vs. descending. Specify list for multiple sort\n",
+      "         orders.  If this is a list of bools, must match the length of\n",
+      "         the by.\n",
+      "    inplace : bool, default False\n",
+      "         If True, perform operation in-place.\n",
+      "    kind : {'quicksort', 'mergesort', 'heapsort'}, default 'quicksort'\n",
+      "         Choice of sorting algorithm. See also ndarray.np.sort for more\n",
+      "         information.  `mergesort` is the only stable algorithm. For\n",
+      "         DataFrames, this option is only applied when sorting on a single\n",
+      "         column or label.\n",
+      "    na_position : {'first', 'last'}, default 'last'\n",
+      "         Puts NaNs at the beginning if `first`; `last` puts NaNs at the\n",
+      "         end.\n",
+      "    ignore_index : bool, default False\n",
+      "         If True, the resulting axis will be labeled 0, 1, …, n - 1.\n",
+      "    \n",
+      "         .. versionadded:: 1.0.0\n",
+      "    \n",
+      "    key : callable, optional\n",
+      "        Apply the key function to the values\n",
+      "        before sorting. This is similar to the `key` argument in the\n",
+      "        builtin :meth:`sorted` function, with the notable difference that\n",
+      "        this `key` function should be *vectorized*. It should expect a\n",
+      "        ``Series`` and return a Series with the same shape as the input.\n",
+      "        It will be applied to each column in `by` independently.\n",
+      "    \n",
+      "        .. versionadded:: 1.1.0\n",
+      "    \n",
+      "    Returns\n",
+      "    -------\n",
+      "    DataFrame or None\n",
+      "        DataFrame with sorted values if inplace=False, None otherwise.\n",
+      "    \n",
+      "    See Also\n",
+      "    --------\n",
+      "    DataFrame.sort_index : Sort a DataFrame by the index.\n",
+      "    Series.sort_values : Similar method for a Series.\n",
+      "    \n",
+      "    Examples\n",
+      "    --------\n",
+      "    >>> df = pd.DataFrame({\n",
+      "    ...     'col1': ['A', 'A', 'B', np.nan, 'D', 'C'],\n",
+      "    ...     'col2': [2, 1, 9, 8, 7, 4],\n",
+      "    ...     'col3': [0, 1, 9, 4, 2, 3],\n",
+      "    ...     'col4': ['a', 'B', 'c', 'D', 'e', 'F']\n",
+      "    ... })\n",
+      "    >>> df\n",
+      "      col1  col2  col3 col4\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    2    B     9     9    c\n",
+      "    3  NaN     8     4    D\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "    \n",
+      "    Sort by col1\n",
+      "    \n",
+      "    >>> df.sort_values(by=['col1'])\n",
+      "      col1  col2  col3 col4\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    2    B     9     9    c\n",
+      "    5    C     4     3    F\n",
+      "    4    D     7     2    e\n",
+      "    3  NaN     8     4    D\n",
+      "    \n",
+      "    Sort by multiple columns\n",
+      "    \n",
+      "    >>> df.sort_values(by=['col1', 'col2'])\n",
+      "      col1  col2  col3 col4\n",
+      "    1    A     1     1    B\n",
+      "    0    A     2     0    a\n",
+      "    2    B     9     9    c\n",
+      "    5    C     4     3    F\n",
+      "    4    D     7     2    e\n",
+      "    3  NaN     8     4    D\n",
+      "    \n",
+      "    Sort Descending\n",
+      "    \n",
+      "    >>> df.sort_values(by='col1', ascending=False)\n",
+      "      col1  col2  col3 col4\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "    2    B     9     9    c\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    3  NaN     8     4    D\n",
+      "    \n",
+      "    Putting NAs first\n",
+      "    \n",
+      "    >>> df.sort_values(by='col1', ascending=False, na_position='first')\n",
+      "      col1  col2  col3 col4\n",
+      "    3  NaN     8     4    D\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "    2    B     9     9    c\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    \n",
+      "    Sorting with a key function\n",
+      "    \n",
+      "    >>> df.sort_values(by='col4', key=lambda col: col.str.lower())\n",
+      "       col1  col2  col3 col4\n",
+      "    0    A     2     0    a\n",
+      "    1    A     1     1    B\n",
+      "    2    B     9     9    c\n",
+      "    3  NaN     8     4    D\n",
+      "    4    D     7     2    e\n",
+      "    5    C     4     3    F\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "help(nba.sort_values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "At the very top of this `help` text, the *signature* of the `sort_value` method appears:\n",
+    "\n",
+    "    sort_value(column_or_label, descending=False, distinct=False)\n",
+    "    \n",
+    "This describes the positions, names, and default values of the three arguments to `sort_value`. When calling this method, you can use either positional arguments or named arguments, so the following three calls do exactly the same thing.\n",
+    "\n",
+    "    sort_value('SALARY', True)\n",
+    "    sort_value('SALARY', ascending=False)\n",
+    "    sort_value(column_or_label='SALARY', ascending=False)\n",
+    "    \n",
+    "When an argument is simply `True` or `False`, it's a useful convention to include the argument name so that it's more obvious what the argument value means."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/2/.ipynb_checkpoints/Selecting_Rows-checkpoint.ipynb

@@ -0,0 +1,1627 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "nba_salaries = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "nba = nba_salaries.rename(columns={\"'15-'16 SALARY\": 'SALARY'})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Selecting Rows\n",
+    "\n",
+    "Often, we would like to extract just those rows that correspond to entries with a particular feature. For example, we might want only the rows corresponding to the Warriors, or to players who earned more than $\\$10$ million. Or we might just want the top five earners."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Specified Rows\n",
+    "The fact that a DataFrame creates an index by default startts to become very useful here as we can specify which rows (by default) we wish to inspect by stating an index or an index range. The argument used a row index or array of indices, and it creates a new DataFrame consisting of only those rows.\n",
+    "\n",
+    "For example, if we wanted just the first row of `nba`, we could use `df.iloc[]` as follows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM     SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks  18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks  12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks   9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks   8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks   5.746479\n",
+       "..               ...      ...                 ...        ...\n",
+       "412        Gary Neal       PG  Washington Wizards   2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards   2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards   1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards   1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards   0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PLAYER       Paul Millsap\n",
+       "POSITION               PF\n",
+       "TEAM        Atlanta Hawks\n",
+       "SALARY            18.6717\n",
+       "Name: 0, dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.iloc[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         PLAYER POSITION           TEAM     SALARY\n",
+       "0  Paul Millsap       PF  Atlanta Hawks  18.671659"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.iloc[[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a new table with just the single row that we specified.\n",
+    "\n",
+    "We could also get the fourth, fifth, and sixth rows by specifying a range of indices as the argument."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Thabo Sefolosha</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>4.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            PLAYER POSITION           TEAM    SALARY\n",
+       "3      Jeff Teague       PG  Atlanta Hawks  8.000000\n",
+       "4      Kyle Korver       SG  Atlanta Hawks  5.746479\n",
+       "5  Thabo Sefolosha       SF  Atlanta Hawks  4.000000"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.iloc[np.arange(3, 6)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we want a table of the top 5 highest paid players, we can first sort the list by salary and then `df.iloc[]` the first five rows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                 TEAM     SALARY\n",
+       "169      Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "29       Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "72      LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "255  Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "131    Dwight Howard        C      Houston Rockets  22.359364"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY', ascending=False).iloc[(np.arange(5))]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Rows Corresponding to a Specified Feature\n",
+    "More often, we will want to access data in a set of rows that have a certain feature, but whose indices we don't know ahead of time. For example, we might want data on all the players who made more than $\\$10$ million, but we don't want to spend time counting rows in the sorted table.\n",
+    "\n",
+    "Array version - if we wish to work with an array we can use `np.where(df['column'] criteria)`.  \n",
+    "\n",
+    "[np.where()](https://numpy.org/doc/stable/reference/generated/numpy.where.html)\n",
+    "\n",
+    "DataFrame version - to implement a selection criteria the df is called with selection criteria being applied to the df.col i.e. `df[df['column_name']criteria]`.\n",
+    "\n",
+    "In the first example, we extract the data for all those who earned more than $\\$10$ million."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([  0,   1,  29,  30,  42,  43,  44,  60,  61,  62,  72,  73,  74,\n",
+       "         75,  76,  82,  83,  93,  94,  95, 107, 117, 118, 119, 120, 121,\n",
+       "        131, 132, 133, 143, 144, 156, 157, 169, 170, 180, 201, 202, 203,\n",
+       "        204, 213, 226, 227, 239, 240, 241, 255, 256, 268, 269, 270, 271,\n",
+       "        284, 285, 298, 311, 312, 342, 343, 353, 354, 355, 366, 367, 368,\n",
+       "        383, 400, 401, 402]),)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.where(nba['SALARY'] > 10)\n",
+    "\n",
+    "# or - this is an example of alternatives being available to select,\n",
+    "# this may depend upon preference, the task at hand, the impact of processing time or export requirements\n",
+    "\n",
+    "#nba[nba['SALARY'] >10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The use of the argument `df[df[col] > 10]` ensured that each selected row had a value of `SALARY` that was greater than 10.\n",
+    "\n",
+    "There are 69 rows in the new table, corresponding to the 69 players who made more than $10$ million dollars. Arranging these rows in order makes the data easier to analyze. DeMar DeRozan of the Toronto Raptors was the \"poorest\" of this group, at a salary of just over $10$ million dollars."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>368</th>\n",
+       "      <td>DeMar DeRozan</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Toronto Raptors</td>\n",
+       "      <td>10.050000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>298</th>\n",
+       "      <td>Gerald Wallace</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Philadelphia 76ers</td>\n",
+       "      <td>10.105855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>204</th>\n",
+       "      <td>Luol Deng</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Miami Heat</td>\n",
+       "      <td>10.151612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>144</th>\n",
+       "      <td>Monta Ellis</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Indiana Pacers</td>\n",
+       "      <td>10.300000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>Wilson Chandler</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Denver Nuggets</td>\n",
+       "      <td>10.449438</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>69 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                 TEAM     SALARY\n",
+       "368    DeMar DeRozan       SG      Toronto Raptors  10.050000\n",
+       "298   Gerald Wallace       SF   Philadelphia 76ers  10.105855\n",
+       "204        Luol Deng       SF           Miami Heat  10.151612\n",
+       "144      Monta Ellis       SG       Indiana Pacers  10.300000\n",
+       "95   Wilson Chandler       SF       Denver Nuggets  10.449438\n",
+       "..               ...      ...                  ...        ...\n",
+       "131    Dwight Howard        C      Houston Rockets  22.359364\n",
+       "255  Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "72      LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "29       Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "169      Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "\n",
+       "[69 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['SALARY'] >10].sort_values('SALARY')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "How much did Stephen Curry make? For the answer, we have to access the row where the value of `PLAYER` is equal to `Stephen Curry`. That is placed a table consisting of just one line:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            PLAYER POSITION                   TEAM     SALARY\n",
+       "121  Stephen Curry       PG  Golden State Warriors  11.370786"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['PLAYER'] == 'Stephen Curry']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Curry made just under $\\$11.4$ million dollars. That's a lot of money, but it's less than half the salary of LeBron James. You'll find that salary in the \"Top 5\" table earlier in this section, or you could find it replacing `'Stephen Curry'` by `'LeBron James'` in the line of code above.\n",
+    "\n",
+    "Thus for example you can get a DataFrame where the 'TEAM' is exactly equal to 'Golden State Warriors':"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['TEAM'] == 'Golden State Warriors']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This portion of the table is already sorted by salary, because the original table listed players sorted by salary within the same team. By not using `.head()` at the end of the line all rows are shown, not just the first 10."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multiple Features\n",
+    "You can access rows that have multiple specified features, by using the boolean `&` operator. For example, here is a way to extract all the Point Guards whose salaries were over $\\$15$ million."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>Derrick Rose</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Chicago Bulls</td>\n",
+       "      <td>20.093064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>74</th>\n",
+       "      <td>Kyrie Irving</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>16.407501</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>156</th>\n",
+       "      <td>Chris Paul</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Los Angeles Clippers</td>\n",
+       "      <td>21.468695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>269</th>\n",
+       "      <td>Russell Westbrook</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Oklahoma City Thunder</td>\n",
+       "      <td>16.744218</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>400</th>\n",
+       "      <td>John Wall</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>15.851950</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "60        Derrick Rose       PG          Chicago Bulls  20.093064\n",
+       "74        Kyrie Irving       PG    Cleveland Cavaliers  16.407501\n",
+       "156         Chris Paul       PG   Los Angeles Clippers  21.468695\n",
+       "269  Russell Westbrook       PG  Oklahoma City Thunder  16.744218\n",
+       "400          John Wall       PG     Washington Wizards  15.851950"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[(nba['POSITION'] == 'PG') & (nba['SALARY'] > 15)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### General Form\n",
+    "By now you will have realized that the general way to create a new df by selecting rows with a given feature is to use `&` or `OR` with the appropriate condition:\n",
+    "\n",
+    "`df[df['column_label_string'] condition(<, >, ==, =>, etc) criteria]`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>144</th>\n",
+       "      <td>Monta Ellis</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Indiana Pacers</td>\n",
+       "      <td>10.300000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>204</th>\n",
+       "      <td>Luol Deng</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Miami Heat</td>\n",
+       "      <td>10.151612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>298</th>\n",
+       "      <td>Gerald Wallace</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Philadelphia 76ers</td>\n",
+       "      <td>10.105855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>356</th>\n",
+       "      <td>Danny Green</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>San Antonio Spurs</td>\n",
+       "      <td>10.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>368</th>\n",
+       "      <td>DeMar DeRozan</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Toronto Raptors</td>\n",
+       "      <td>10.050000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             PLAYER POSITION                TEAM     SALARY\n",
+       "144     Monta Ellis       SG      Indiana Pacers  10.300000\n",
+       "204       Luol Deng       SF          Miami Heat  10.151612\n",
+       "298  Gerald Wallace       SF  Philadelphia 76ers  10.105855\n",
+       "356     Danny Green       SG   San Antonio Spurs  10.000000\n",
+       "368   DeMar DeRozan       SG     Toronto Raptors  10.050000"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[(nba['SALARY'] >= 10) & (nba['SALARY'] <=10.3)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we specify a condition that isn't satisfied by any row, we get a table with column labels but no rows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [PLAYER, POSITION, TEAM, SALARY]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['PLAYER'] == 'Barack Obama']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We end the section with a series of examples. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The use of `are.containing` can help save some typing. For example, you can just specify `Warriors` instead of `Golden State Warriors`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['TEAM'].str.contains('Warriors')]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can extract data for all the guards, both Point Guards and Shooting Guards:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Dennis Schroder</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>1.763400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Tim Hardaway Jr.</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>1.304520</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Jason Richardson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>0.947276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>409</th>\n",
+       "      <td>Alan Anderson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>4.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>411</th>\n",
+       "      <td>Ramon Sessions</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.170465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>181 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               PLAYER POSITION                TEAM    SALARY\n",
+       "3         Jeff Teague       PG       Atlanta Hawks  8.000000\n",
+       "4         Kyle Korver       SG       Atlanta Hawks  5.746479\n",
+       "8     Dennis Schroder       PG       Atlanta Hawks  1.763400\n",
+       "9    Tim Hardaway Jr.       SG       Atlanta Hawks  1.304520\n",
+       "11   Jason Richardson       SG       Atlanta Hawks  0.947276\n",
+       "..                ...      ...                 ...       ...\n",
+       "409     Alan Anderson       SG  Washington Wizards  4.000000\n",
+       "411    Ramon Sessions       PG  Washington Wizards  2.170465\n",
+       "412         Gary Neal       PG  Washington Wizards  2.139000\n",
+       "415    Garrett Temple       SG  Washington Wizards  1.100602\n",
+       "416      Jarell Eddie       SG  Washington Wizards  0.561716\n",
+       "\n",
+       "[181 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['POSITION'].str.contains('G')]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can get all the players who were not Cleveland Cavaliers and had a salary of no less than $\\$20$ million:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>Derrick Rose</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Chicago Bulls</td>\n",
+       "      <td>20.093064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>156</th>\n",
+       "      <td>Chris Paul</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Los Angeles Clippers</td>\n",
+       "      <td>21.468695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>201</th>\n",
+       "      <td>Chris Bosh</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Miami Heat</td>\n",
+       "      <td>22.192730</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>268</th>\n",
+       "      <td>Kevin Durant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Oklahoma City Thunder</td>\n",
+       "      <td>20.158622</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                   TEAM     SALARY\n",
+       "29       Joe Johnson       SF          Brooklyn Nets  24.894863\n",
+       "60      Derrick Rose       PG          Chicago Bulls  20.093064\n",
+       "131    Dwight Howard        C        Houston Rockets  22.359364\n",
+       "156       Chris Paul       PG   Los Angeles Clippers  21.468695\n",
+       "169      Kobe Bryant       SF     Los Angeles Lakers  25.000000\n",
+       "201       Chris Bosh       PF             Miami Heat  22.192730\n",
+       "255  Carmelo Anthony       SF        New York Knicks  22.875000\n",
+       "268     Kevin Durant       SF  Oklahoma City Thunder  20.158622"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "other_than_Cavs = nba[nba['TEAM'] != 'Cleveland Cavaliers']\n",
+    "other_than_Cavs[other_than_Cavs['SALARY']  > 20]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The same table can be created in many ways. Here is another, and no doubt you can think of more."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/2/Selecting_Rows.ipynb

@@ -0,0 +1,1627 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "nba_salaries = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "nba = nba_salaries.rename(columns={\"'15-'16 SALARY\": 'SALARY'})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Selecting Rows\n",
+    "\n",
+    "Often, we would like to extract just those rows that correspond to entries with a particular feature. For example, we might want only the rows corresponding to the Warriors, or to players who earned more than $\\$10$ million. Or we might just want the top five earners."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Specified Rows\n",
+    "The fact that a DataFrame creates an index by default startts to become very useful here as we can specify which rows (by default) we wish to inspect by stating an index or an index range. The argument used a row index or array of indices, and it creates a new DataFrame consisting of only those rows.\n",
+    "\n",
+    "For example, if we wanted just the first row of `nba`, we could use `df.iloc[]` as follows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM     SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks  18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks  12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks   9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks   8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks   5.746479\n",
+       "..               ...      ...                 ...        ...\n",
+       "412        Gary Neal       PG  Washington Wizards   2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards   2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards   1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards   1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards   0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PLAYER       Paul Millsap\n",
+       "POSITION               PF\n",
+       "TEAM        Atlanta Hawks\n",
+       "SALARY            18.6717\n",
+       "Name: 0, dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.iloc[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         PLAYER POSITION           TEAM     SALARY\n",
+       "0  Paul Millsap       PF  Atlanta Hawks  18.671659"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.iloc[[0]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a new table with just the single row that we specified.\n",
+    "\n",
+    "We could also get the fourth, fifth, and sixth rows by specifying a range of indices as the argument."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Thabo Sefolosha</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>4.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            PLAYER POSITION           TEAM    SALARY\n",
+       "3      Jeff Teague       PG  Atlanta Hawks  8.000000\n",
+       "4      Kyle Korver       SG  Atlanta Hawks  5.746479\n",
+       "5  Thabo Sefolosha       SF  Atlanta Hawks  4.000000"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.iloc[np.arange(3, 6)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we want a table of the top 5 highest paid players, we can first sort the list by salary and then `df.iloc[]` the first five rows:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                 TEAM     SALARY\n",
+       "169      Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "29       Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "72      LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "255  Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "131    Dwight Howard        C      Houston Rockets  22.359364"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba.sort_values('SALARY', ascending=False).iloc[(np.arange(5))]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Rows Corresponding to a Specified Feature\n",
+    "More often, we will want to access data in a set of rows that have a certain feature, but whose indices we don't know ahead of time. For example, we might want data on all the players who made more than $\\$10$ million, but we don't want to spend time counting rows in the sorted table.\n",
+    "\n",
+    "Array version - if we wish to work with an array we can use `np.where(df['column'] criteria)`.  \n",
+    "\n",
+    "[np.where()](https://numpy.org/doc/stable/reference/generated/numpy.where.html)\n",
+    "\n",
+    "DataFrame version - to implement a selection criteria the df is called with selection criteria being applied to the df.col i.e. `df[df['column_name']criteria]`.\n",
+    "\n",
+    "In the first example, we extract the data for all those who earned more than $\\$10$ million."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([  0,   1,  29,  30,  42,  43,  44,  60,  61,  62,  72,  73,  74,\n",
+       "         75,  76,  82,  83,  93,  94,  95, 107, 117, 118, 119, 120, 121,\n",
+       "        131, 132, 133, 143, 144, 156, 157, 169, 170, 180, 201, 202, 203,\n",
+       "        204, 213, 226, 227, 239, 240, 241, 255, 256, 268, 269, 270, 271,\n",
+       "        284, 285, 298, 311, 312, 342, 343, 353, 354, 355, 366, 367, 368,\n",
+       "        383, 400, 401, 402]),)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.where(nba['SALARY'] > 10)\n",
+    "\n",
+    "# or - this is an example of alternatives being available to select,\n",
+    "# this may depend upon preference, the task at hand, the impact of processing time or export requirements\n",
+    "\n",
+    "#nba[nba['SALARY'] >10]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The use of the argument `df[df[col] > 10]` ensured that each selected row had a value of `SALARY` that was greater than 10.\n",
+    "\n",
+    "There are 69 rows in the new table, corresponding to the 69 players who made more than $10$ million dollars. Arranging these rows in order makes the data easier to analyze. DeMar DeRozan of the Toronto Raptors was the \"poorest\" of this group, at a salary of just over $10$ million dollars."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>368</th>\n",
+       "      <td>DeMar DeRozan</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Toronto Raptors</td>\n",
+       "      <td>10.050000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>298</th>\n",
+       "      <td>Gerald Wallace</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Philadelphia 76ers</td>\n",
+       "      <td>10.105855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>204</th>\n",
+       "      <td>Luol Deng</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Miami Heat</td>\n",
+       "      <td>10.151612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>144</th>\n",
+       "      <td>Monta Ellis</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Indiana Pacers</td>\n",
+       "      <td>10.300000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>Wilson Chandler</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Denver Nuggets</td>\n",
+       "      <td>10.449438</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>72</th>\n",
+       "      <td>LeBron James</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>22.970500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>69 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                 TEAM     SALARY\n",
+       "368    DeMar DeRozan       SG      Toronto Raptors  10.050000\n",
+       "298   Gerald Wallace       SF   Philadelphia 76ers  10.105855\n",
+       "204        Luol Deng       SF           Miami Heat  10.151612\n",
+       "144      Monta Ellis       SG       Indiana Pacers  10.300000\n",
+       "95   Wilson Chandler       SF       Denver Nuggets  10.449438\n",
+       "..               ...      ...                  ...        ...\n",
+       "131    Dwight Howard        C      Houston Rockets  22.359364\n",
+       "255  Carmelo Anthony       SF      New York Knicks  22.875000\n",
+       "72      LeBron James       SF  Cleveland Cavaliers  22.970500\n",
+       "29       Joe Johnson       SF        Brooklyn Nets  24.894863\n",
+       "169      Kobe Bryant       SF   Los Angeles Lakers  25.000000\n",
+       "\n",
+       "[69 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['SALARY'] >10].sort_values('SALARY')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "How much did Stephen Curry make? For the answer, we have to access the row where the value of `PLAYER` is equal to `Stephen Curry`. That is placed a table consisting of just one line:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            PLAYER POSITION                   TEAM     SALARY\n",
+       "121  Stephen Curry       PG  Golden State Warriors  11.370786"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['PLAYER'] == 'Stephen Curry']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Curry made just under $\\$11.4$ million dollars. That's a lot of money, but it's less than half the salary of LeBron James. You'll find that salary in the \"Top 5\" table earlier in this section, or you could find it replacing `'Stephen Curry'` by `'LeBron James'` in the line of code above.\n",
+    "\n",
+    "Thus for example you can get a DataFrame where the 'TEAM' is exactly equal to 'Golden State Warriors':"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['TEAM'] == 'Golden State Warriors']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This portion of the table is already sorted by salary, because the original table listed players sorted by salary within the same team. By not using `.head()` at the end of the line all rows are shown, not just the first 10."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multiple Features\n",
+    "You can access rows that have multiple specified features, by using the boolean `&` operator. For example, here is a way to extract all the Point Guards whose salaries were over $\\$15$ million."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>Derrick Rose</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Chicago Bulls</td>\n",
+       "      <td>20.093064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>74</th>\n",
+       "      <td>Kyrie Irving</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Cleveland Cavaliers</td>\n",
+       "      <td>16.407501</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>156</th>\n",
+       "      <td>Chris Paul</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Los Angeles Clippers</td>\n",
+       "      <td>21.468695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>269</th>\n",
+       "      <td>Russell Westbrook</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Oklahoma City Thunder</td>\n",
+       "      <td>16.744218</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>400</th>\n",
+       "      <td>John Wall</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>15.851950</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "60        Derrick Rose       PG          Chicago Bulls  20.093064\n",
+       "74        Kyrie Irving       PG    Cleveland Cavaliers  16.407501\n",
+       "156         Chris Paul       PG   Los Angeles Clippers  21.468695\n",
+       "269  Russell Westbrook       PG  Oklahoma City Thunder  16.744218\n",
+       "400          John Wall       PG     Washington Wizards  15.851950"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[(nba['POSITION'] == 'PG') & (nba['SALARY'] > 15)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### General Form\n",
+    "By now you will have realized that the general way to create a new df by selecting rows with a given feature is to use `&` or `OR` with the appropriate condition:\n",
+    "\n",
+    "`df[df['column_label_string'] condition(<, >, ==, =>, etc) criteria]`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>144</th>\n",
+       "      <td>Monta Ellis</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Indiana Pacers</td>\n",
+       "      <td>10.300000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>204</th>\n",
+       "      <td>Luol Deng</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Miami Heat</td>\n",
+       "      <td>10.151612</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>298</th>\n",
+       "      <td>Gerald Wallace</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Philadelphia 76ers</td>\n",
+       "      <td>10.105855</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>356</th>\n",
+       "      <td>Danny Green</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>San Antonio Spurs</td>\n",
+       "      <td>10.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>368</th>\n",
+       "      <td>DeMar DeRozan</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Toronto Raptors</td>\n",
+       "      <td>10.050000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             PLAYER POSITION                TEAM     SALARY\n",
+       "144     Monta Ellis       SG      Indiana Pacers  10.300000\n",
+       "204       Luol Deng       SF          Miami Heat  10.151612\n",
+       "298  Gerald Wallace       SF  Philadelphia 76ers  10.105855\n",
+       "356     Danny Green       SG   San Antonio Spurs  10.000000\n",
+       "368   DeMar DeRozan       SG     Toronto Raptors  10.050000"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[(nba['SALARY'] >= 10) & (nba['SALARY'] <=10.3)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "If we specify a condition that isn't satisfied by any row, we get a table with column labels but no rows."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [PLAYER, POSITION, TEAM, SALARY]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['PLAYER'] == 'Barack Obama']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We end the section with a series of examples. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The use of `are.containing` can help save some typing. For example, you can just specify `Warriors` instead of `Golden State Warriors`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>117</th>\n",
+       "      <td>Klay Thompson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>15.501000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>Draymond Green</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>14.260870</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>Andrew Bogut</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>13.800000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>Andre Iguodala</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.710456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>Stephen Curry</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>11.370786</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>Jason Thompson</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>7.008475</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>123</th>\n",
+       "      <td>Shaun Livingston</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>5.543725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>124</th>\n",
+       "      <td>Harrison Barnes</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.873398</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>125</th>\n",
+       "      <td>Marreese Speights</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>3.815000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>126</th>\n",
+       "      <td>Leandro Barbosa</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>127</th>\n",
+       "      <td>Festus Ezeli</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>2.008748</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>128</th>\n",
+       "      <td>Brandon Rush</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.270964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>129</th>\n",
+       "      <td>Kevon Looney</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>1.131960</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>130</th>\n",
+       "      <td>Anderson Varejao</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Golden State Warriors</td>\n",
+       "      <td>0.289755</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                PLAYER POSITION                   TEAM     SALARY\n",
+       "117      Klay Thompson       SG  Golden State Warriors  15.501000\n",
+       "118     Draymond Green       PF  Golden State Warriors  14.260870\n",
+       "119       Andrew Bogut        C  Golden State Warriors  13.800000\n",
+       "120     Andre Iguodala       SF  Golden State Warriors  11.710456\n",
+       "121      Stephen Curry       PG  Golden State Warriors  11.370786\n",
+       "122     Jason Thompson       PF  Golden State Warriors   7.008475\n",
+       "123   Shaun Livingston       PG  Golden State Warriors   5.543725\n",
+       "124    Harrison Barnes       SF  Golden State Warriors   3.873398\n",
+       "125  Marreese Speights        C  Golden State Warriors   3.815000\n",
+       "126    Leandro Barbosa       SG  Golden State Warriors   2.500000\n",
+       "127       Festus Ezeli        C  Golden State Warriors   2.008748\n",
+       "128       Brandon Rush       SF  Golden State Warriors   1.270964\n",
+       "129       Kevon Looney       SF  Golden State Warriors   1.131960\n",
+       "130   Anderson Varejao       PF  Golden State Warriors   0.289755"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['TEAM'].str.contains('Warriors')]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can extract data for all the guards, both Point Guards and Shooting Guards:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Dennis Schroder</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>1.763400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Tim Hardaway Jr.</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>1.304520</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Jason Richardson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>0.947276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>409</th>\n",
+       "      <td>Alan Anderson</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>4.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>411</th>\n",
+       "      <td>Ramon Sessions</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.170465</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>181 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               PLAYER POSITION                TEAM    SALARY\n",
+       "3         Jeff Teague       PG       Atlanta Hawks  8.000000\n",
+       "4         Kyle Korver       SG       Atlanta Hawks  5.746479\n",
+       "8     Dennis Schroder       PG       Atlanta Hawks  1.763400\n",
+       "9    Tim Hardaway Jr.       SG       Atlanta Hawks  1.304520\n",
+       "11   Jason Richardson       SG       Atlanta Hawks  0.947276\n",
+       "..                ...      ...                 ...       ...\n",
+       "409     Alan Anderson       SG  Washington Wizards  4.000000\n",
+       "411    Ramon Sessions       PG  Washington Wizards  2.170465\n",
+       "412         Gary Neal       PG  Washington Wizards  2.139000\n",
+       "415    Garrett Temple       SG  Washington Wizards  1.100602\n",
+       "416      Jarell Eddie       SG  Washington Wizards  0.561716\n",
+       "\n",
+       "[181 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba[nba['POSITION'].str.contains('G')]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can get all the players who were not Cleveland Cavaliers and had a salary of no less than $\\$20$ million:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>29</th>\n",
+       "      <td>Joe Johnson</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Brooklyn Nets</td>\n",
+       "      <td>24.894863</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60</th>\n",
+       "      <td>Derrick Rose</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Chicago Bulls</td>\n",
+       "      <td>20.093064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>131</th>\n",
+       "      <td>Dwight Howard</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Houston Rockets</td>\n",
+       "      <td>22.359364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>156</th>\n",
+       "      <td>Chris Paul</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Los Angeles Clippers</td>\n",
+       "      <td>21.468695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>169</th>\n",
+       "      <td>Kobe Bryant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Los Angeles Lakers</td>\n",
+       "      <td>25.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>201</th>\n",
+       "      <td>Chris Bosh</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Miami Heat</td>\n",
+       "      <td>22.192730</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>255</th>\n",
+       "      <td>Carmelo Anthony</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>New York Knicks</td>\n",
+       "      <td>22.875000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>268</th>\n",
+       "      <td>Kevin Durant</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Oklahoma City Thunder</td>\n",
+       "      <td>20.158622</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                   TEAM     SALARY\n",
+       "29       Joe Johnson       SF          Brooklyn Nets  24.894863\n",
+       "60      Derrick Rose       PG          Chicago Bulls  20.093064\n",
+       "131    Dwight Howard        C        Houston Rockets  22.359364\n",
+       "156       Chris Paul       PG   Los Angeles Clippers  21.468695\n",
+       "169      Kobe Bryant       SF     Los Angeles Lakers  25.000000\n",
+       "201       Chris Bosh       PF             Miami Heat  22.192730\n",
+       "255  Carmelo Anthony       SF        New York Knicks  22.875000\n",
+       "268     Kevin Durant       SF  Oklahoma City Thunder  20.158622"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "other_than_Cavs = nba[nba['TEAM'] != 'Cleveland Cavaliers']\n",
+    "other_than_Cavs[other_than_Cavs['SALARY']  > 20]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The same table can be created in many ways. Here is another, and no doubt you can think of more."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/3/.ipynb_checkpoints/Example_Trends_in_the_Population_of_the_United_States-checkpoint.ipynb

@@ -0,0 +1,6239 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Example: Population Trends\n",
+    "\n",
+    "We are now ready to work with large tables of data. The file below contains \"Annual Estimates of the Resident Population by Single Year of Age and Sex for the United States.\" Notice that `read_table` can read data directly from a URL."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>CENSUS2010POP</th>\n",
+       "      <th>ESTIMATESBASE2010</th>\n",
+       "      <th>POPESTIMATE2010</th>\n",
+       "      <th>POPESTIMATE2011</th>\n",
+       "      <th>POPESTIMATE2012</th>\n",
+       "      <th>POPESTIMATE2013</th>\n",
+       "      <th>POPESTIMATE2014</th>\n",
+       "      <th>POPESTIMATE2015</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3944153</td>\n",
+       "      <td>3944160</td>\n",
+       "      <td>3951330</td>\n",
+       "      <td>3963087</td>\n",
+       "      <td>3926540</td>\n",
+       "      <td>3931141</td>\n",
+       "      <td>3949775</td>\n",
+       "      <td>3978038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3978070</td>\n",
+       "      <td>3978090</td>\n",
+       "      <td>3957888</td>\n",
+       "      <td>3966551</td>\n",
+       "      <td>3977939</td>\n",
+       "      <td>3942872</td>\n",
+       "      <td>3949776</td>\n",
+       "      <td>3968564</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4096929</td>\n",
+       "      <td>4096939</td>\n",
+       "      <td>4090862</td>\n",
+       "      <td>3971565</td>\n",
+       "      <td>3980095</td>\n",
+       "      <td>3992720</td>\n",
+       "      <td>3959664</td>\n",
+       "      <td>3966583</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4119040</td>\n",
+       "      <td>4119051</td>\n",
+       "      <td>4111920</td>\n",
+       "      <td>4102470</td>\n",
+       "      <td>3983157</td>\n",
+       "      <td>3992734</td>\n",
+       "      <td>4007079</td>\n",
+       "      <td>3974061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4063170</td>\n",
+       "      <td>4063186</td>\n",
+       "      <td>4077551</td>\n",
+       "      <td>4122294</td>\n",
+       "      <td>4112849</td>\n",
+       "      <td>3994449</td>\n",
+       "      <td>4005716</td>\n",
+       "      <td>4020035</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>301</th>\n",
+       "      <td>2</td>\n",
+       "      <td>97</td>\n",
+       "      <td>53582</td>\n",
+       "      <td>53605</td>\n",
+       "      <td>54118</td>\n",
+       "      <td>57159</td>\n",
+       "      <td>59533</td>\n",
+       "      <td>61255</td>\n",
+       "      <td>62779</td>\n",
+       "      <td>69285</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>302</th>\n",
+       "      <td>2</td>\n",
+       "      <td>98</td>\n",
+       "      <td>36641</td>\n",
+       "      <td>36675</td>\n",
+       "      <td>37532</td>\n",
+       "      <td>40116</td>\n",
+       "      <td>42857</td>\n",
+       "      <td>44359</td>\n",
+       "      <td>46208</td>\n",
+       "      <td>47272</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>2</td>\n",
+       "      <td>99</td>\n",
+       "      <td>26193</td>\n",
+       "      <td>26214</td>\n",
+       "      <td>26074</td>\n",
+       "      <td>27030</td>\n",
+       "      <td>29320</td>\n",
+       "      <td>31112</td>\n",
+       "      <td>32517</td>\n",
+       "      <td>34064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>304</th>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>44202</td>\n",
+       "      <td>44246</td>\n",
+       "      <td>45058</td>\n",
+       "      <td>47556</td>\n",
+       "      <td>50661</td>\n",
+       "      <td>53902</td>\n",
+       "      <td>58008</td>\n",
+       "      <td>61886</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>305</th>\n",
+       "      <td>2</td>\n",
+       "      <td>999</td>\n",
+       "      <td>156964212</td>\n",
+       "      <td>156969328</td>\n",
+       "      <td>157258820</td>\n",
+       "      <td>158427085</td>\n",
+       "      <td>159581546</td>\n",
+       "      <td>160720625</td>\n",
+       "      <td>161952064</td>\n",
+       "      <td>163189523</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>306 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     SEX  AGE  CENSUS2010POP  ESTIMATESBASE2010  POPESTIMATE2010  \\\n",
+       "0      0    0        3944153            3944160          3951330   \n",
+       "1      0    1        3978070            3978090          3957888   \n",
+       "2      0    2        4096929            4096939          4090862   \n",
+       "3      0    3        4119040            4119051          4111920   \n",
+       "4      0    4        4063170            4063186          4077551   \n",
+       "..   ...  ...            ...                ...              ...   \n",
+       "301    2   97          53582              53605            54118   \n",
+       "302    2   98          36641              36675            37532   \n",
+       "303    2   99          26193              26214            26074   \n",
+       "304    2  100          44202              44246            45058   \n",
+       "305    2  999      156964212          156969328        157258820   \n",
+       "\n",
+       "     POPESTIMATE2011  POPESTIMATE2012  POPESTIMATE2013  POPESTIMATE2014  \\\n",
+       "0            3963087          3926540          3931141          3949775   \n",
+       "1            3966551          3977939          3942872          3949776   \n",
+       "2            3971565          3980095          3992720          3959664   \n",
+       "3            4102470          3983157          3992734          4007079   \n",
+       "4            4122294          4112849          3994449          4005716   \n",
+       "..               ...              ...              ...              ...   \n",
+       "301            57159            59533            61255            62779   \n",
+       "302            40116            42857            44359            46208   \n",
+       "303            27030            29320            31112            32517   \n",
+       "304            47556            50661            53902            58008   \n",
+       "305        158427085        159581546        160720625        161952064   \n",
+       "\n",
+       "     POPESTIMATE2015  \n",
+       "0            3978038  \n",
+       "1            3968564  \n",
+       "2            3966583  \n",
+       "3            3974061  \n",
+       "4            4020035  \n",
+       "..               ...  \n",
+       "301            69285  \n",
+       "302            47272  \n",
+       "303            34064  \n",
+       "304            61886  \n",
+       "305        163189523  \n",
+       "\n",
+       "[306 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# As of Jan 2017, this census file is online here: \n",
+    "data = 'http://www2.census.gov/programs-surveys/popest/datasets/2010-2015/national/asrh/nc-est2015-agesex-res.csv'\n",
+    "\n",
+    "# A local copy can be accessed here in case census.gov moves the file:\n",
+    "# data = path_data + 'nc-est2015-agesex-res.csv'\n",
+    "\n",
+    "full_census_table = pd.read_csv(data)\n",
+    "full_census_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Only the first 5 and last 5 rows of the DataFrame are displayed. Later we will see how to display the entire DataFrame; however, this is typically not useful with large tables.\n",
+    "\n",
+    "a [description of the table](http://www2.census.gov/programs-surveys/popest/datasets/2010-2015/national/asrh/nc-est2015-agesex-res.pdf) appears online. The `SEX` column contains numeric codes: `0` stands for the total, `1` for male, and `2` for female. The `AGE` column contains ages in completed years, but the special value `999` is a sum of the total population. The rest of the columns contain estimates of the US population.\n",
+    "\n",
+    "Typically, a public table will contain more information than necessary for a particular investigation or analysis. In this case, let us suppose that we are only interested in the population changes from 2010 to 2014. Let us `select` the relevant columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>POPESTIMATE2010</th>\n",
+       "      <th>POPESTIMATE2014</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3951330</td>\n",
+       "      <td>3949775</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3957888</td>\n",
+       "      <td>3949776</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4090862</td>\n",
+       "      <td>3959664</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4111920</td>\n",
+       "      <td>4007079</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4077551</td>\n",
+       "      <td>4005716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>301</th>\n",
+       "      <td>2</td>\n",
+       "      <td>97</td>\n",
+       "      <td>54118</td>\n",
+       "      <td>62779</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>302</th>\n",
+       "      <td>2</td>\n",
+       "      <td>98</td>\n",
+       "      <td>37532</td>\n",
+       "      <td>46208</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>2</td>\n",
+       "      <td>99</td>\n",
+       "      <td>26074</td>\n",
+       "      <td>32517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>304</th>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>45058</td>\n",
+       "      <td>58008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>305</th>\n",
+       "      <td>2</td>\n",
+       "      <td>999</td>\n",
+       "      <td>157258820</td>\n",
+       "      <td>161952064</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>306 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     SEX  AGE  POPESTIMATE2010  POPESTIMATE2014\n",
+       "0      0    0          3951330          3949775\n",
+       "1      0    1          3957888          3949776\n",
+       "2      0    2          4090862          3959664\n",
+       "3      0    3          4111920          4007079\n",
+       "4      0    4          4077551          4005716\n",
+       "..   ...  ...              ...              ...\n",
+       "301    2   97            54118            62779\n",
+       "302    2   98            37532            46208\n",
+       "303    2   99            26074            32517\n",
+       "304    2  100            45058            58008\n",
+       "305    2  999        157258820        161952064\n",
+       "\n",
+       "[306 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "partial_census_table = full_census_table[['SEX', 'AGE', 'POPESTIMATE2010', 'POPESTIMATE2014']]\n",
+    "partial_census_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also simplify the labels of the selected columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>2010</th>\n",
+       "      <th>2014</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3951330</td>\n",
+       "      <td>3949775</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3957888</td>\n",
+       "      <td>3949776</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4090862</td>\n",
+       "      <td>3959664</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4111920</td>\n",
+       "      <td>4007079</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4077551</td>\n",
+       "      <td>4005716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>301</th>\n",
+       "      <td>2</td>\n",
+       "      <td>97</td>\n",
+       "      <td>54118</td>\n",
+       "      <td>62779</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>302</th>\n",
+       "      <td>2</td>\n",
+       "      <td>98</td>\n",
+       "      <td>37532</td>\n",
+       "      <td>46208</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>2</td>\n",
+       "      <td>99</td>\n",
+       "      <td>26074</td>\n",
+       "      <td>32517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>304</th>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>45058</td>\n",
+       "      <td>58008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>305</th>\n",
+       "      <td>2</td>\n",
+       "      <td>999</td>\n",
+       "      <td>157258820</td>\n",
+       "      <td>161952064</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>306 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     SEX  AGE       2010       2014\n",
+       "0      0    0    3951330    3949775\n",
+       "1      0    1    3957888    3949776\n",
+       "2      0    2    4090862    3959664\n",
+       "3      0    3    4111920    4007079\n",
+       "4      0    4    4077551    4005716\n",
+       "..   ...  ...        ...        ...\n",
+       "301    2   97      54118      62779\n",
+       "302    2   98      37532      46208\n",
+       "303    2   99      26074      32517\n",
+       "304    2  100      45058      58008\n",
+       "305    2  999  157258820  161952064\n",
+       "\n",
+       "[306 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "us_pop = partial_census_table.rename(columns={'POPESTIMATE2010': '2010', 'POPESTIMATE2014':'2014'})\n",
+    "us_pop"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now have a table that is easy to work with. Each column of the table is an array of the same length, and so columns can be combined using arithmetic. Here is the change in population between 2010 and 2014."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        -1555\n",
+       "1        -8112\n",
+       "2      -131198\n",
+       "3      -104841\n",
+       "4       -71835\n",
+       "        ...   \n",
+       "301       8661\n",
+       "302       8676\n",
+       "303       6443\n",
+       "304      12950\n",
+       "305    4693244\n",
+       "Length: 306, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "us_pop['2014'] - us_pop['2010']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us augment `us_pop` with a column that contains these changes, both in absolute terms and as percents relative to the value in 2010."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >SEX</th>        <th class=\"col_heading level0 col1\" >AGE</th>        <th class=\"col_heading level0 col2\" >2010</th>        <th class=\"col_heading level0 col3\" >2014</th>        <th class=\"col_heading level0 col4\" >Change</th>        <th class=\"col_heading level0 col5\" >Percent Change</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col0\" class=\"data row0 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col1\" class=\"data row0 col1\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col2\" class=\"data row0 col2\" >3951330</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col3\" class=\"data row0 col3\" >3949775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col4\" class=\"data row0 col4\" >-1555</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col5\" class=\"data row0 col5\" >-0.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col0\" class=\"data row1 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col1\" class=\"data row1 col1\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col2\" class=\"data row1 col2\" >3957888</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col3\" class=\"data row1 col3\" >3949776</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col4\" class=\"data row1 col4\" >-8112</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col5\" class=\"data row1 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col0\" class=\"data row2 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col1\" class=\"data row2 col1\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col2\" class=\"data row2 col2\" >4090862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col3\" class=\"data row2 col3\" >3959664</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col4\" class=\"data row2 col4\" >-131198</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col5\" class=\"data row2 col5\" >-3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col0\" class=\"data row3 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col1\" class=\"data row3 col1\" >3</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col2\" class=\"data row3 col2\" >4111920</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col3\" class=\"data row3 col3\" >4007079</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col4\" class=\"data row3 col4\" >-104841</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col5\" class=\"data row3 col5\" >-2.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col0\" class=\"data row4 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col1\" class=\"data row4 col1\" >4</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col2\" class=\"data row4 col2\" >4077551</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col3\" class=\"data row4 col3\" >4005716</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col4\" class=\"data row4 col4\" >-71835</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col5\" class=\"data row4 col5\" >-1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col0\" class=\"data row5 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col1\" class=\"data row5 col1\" >5</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col2\" class=\"data row5 col2\" >4064653</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col3\" class=\"data row5 col3\" >4006900</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col4\" class=\"data row5 col4\" >-57753</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col5\" class=\"data row5 col5\" >-1.42%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col0\" class=\"data row6 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col1\" class=\"data row6 col1\" >6</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col2\" class=\"data row6 col2\" >4073013</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col3\" class=\"data row6 col3\" >4135930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col4\" class=\"data row6 col4\" >62917</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col5\" class=\"data row6 col5\" >1.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col0\" class=\"data row7 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col1\" class=\"data row7 col1\" >7</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col2\" class=\"data row7 col2\" >4043046</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col3\" class=\"data row7 col3\" >4155326</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col4\" class=\"data row7 col4\" >112280</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col5\" class=\"data row7 col5\" >2.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col0\" class=\"data row8 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col1\" class=\"data row8 col1\" >8</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col2\" class=\"data row8 col2\" >4025604</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col3\" class=\"data row8 col3\" >4120903</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col4\" class=\"data row8 col4\" >95299</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col5\" class=\"data row8 col5\" >2.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col0\" class=\"data row9 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col1\" class=\"data row9 col1\" >9</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col2\" class=\"data row9 col2\" >4125415</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col3\" class=\"data row9 col3\" >4108349</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col4\" class=\"data row9 col4\" >-17066</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col5\" class=\"data row9 col5\" >-0.41%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col0\" class=\"data row10 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col1\" class=\"data row10 col1\" >10</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col2\" class=\"data row10 col2\" >4187062</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col3\" class=\"data row10 col3\" >4116942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col4\" class=\"data row10 col4\" >-70120</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col5\" class=\"data row10 col5\" >-1.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col0\" class=\"data row11 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col1\" class=\"data row11 col1\" >11</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col2\" class=\"data row11 col2\" >4115511</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col3\" class=\"data row11 col3\" >4087402</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col4\" class=\"data row11 col4\" >-28109</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col5\" class=\"data row11 col5\" >-0.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col0\" class=\"data row12 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col1\" class=\"data row12 col1\" >12</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col2\" class=\"data row12 col2\" >4113279</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col3\" class=\"data row12 col3\" >4070682</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col4\" class=\"data row12 col4\" >-42597</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col5\" class=\"data row12 col5\" >-1.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col0\" class=\"data row13 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col1\" class=\"data row13 col1\" >13</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col2\" class=\"data row13 col2\" >4119666</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col3\" class=\"data row13 col3\" >4171030</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col4\" class=\"data row13 col4\" >51364</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col5\" class=\"data row13 col5\" >1.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col0\" class=\"data row14 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col1\" class=\"data row14 col1\" >14</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col2\" class=\"data row14 col2\" >4145614</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col3\" class=\"data row14 col3\" >4233839</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col4\" class=\"data row14 col4\" >88225</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col5\" class=\"data row14 col5\" >2.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col0\" class=\"data row15 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col1\" class=\"data row15 col1\" >15</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col2\" class=\"data row15 col2\" >4231002</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col3\" class=\"data row15 col3\" >4164796</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col4\" class=\"data row15 col4\" >-66206</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col5\" class=\"data row15 col5\" >-1.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col0\" class=\"data row16 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col1\" class=\"data row16 col1\" >16</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col2\" class=\"data row16 col2\" >4313252</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col3\" class=\"data row16 col3\" >4168559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col4\" class=\"data row16 col4\" >-144693</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col5\" class=\"data row16 col5\" >-3.35%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col0\" class=\"data row17 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col1\" class=\"data row17 col1\" >17</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col2\" class=\"data row17 col2\" >4376367</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col3\" class=\"data row17 col3\" >4186513</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col4\" class=\"data row17 col4\" >-189854</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col5\" class=\"data row17 col5\" >-4.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col0\" class=\"data row18 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col1\" class=\"data row18 col1\" >18</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col2\" class=\"data row18 col2\" >4491005</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col3\" class=\"data row18 col3\" >4227920</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col4\" class=\"data row18 col4\" >-263085</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col5\" class=\"data row18 col5\" >-5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col0\" class=\"data row19 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col1\" class=\"data row19 col1\" >19</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col2\" class=\"data row19 col2\" >4571411</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col3\" class=\"data row19 col3\" >4329038</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col4\" class=\"data row19 col4\" >-242373</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col5\" class=\"data row19 col5\" >-5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col0\" class=\"data row20 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col1\" class=\"data row20 col1\" >20</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col2\" class=\"data row20 col2\" >4568517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col3\" class=\"data row20 col3\" >4421330</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col4\" class=\"data row20 col4\" >-147187</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col5\" class=\"data row20 col5\" >-3.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col0\" class=\"data row21 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col1\" class=\"data row21 col1\" >21</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col2\" class=\"data row21 col2\" >4387956</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col3\" class=\"data row21 col3\" >4492373</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col4\" class=\"data row21 col4\" >104417</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col5\" class=\"data row21 col5\" >2.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col0\" class=\"data row22 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col1\" class=\"data row22 col1\" >22</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col2\" class=\"data row22 col2\" >4287005</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col3\" class=\"data row22 col3\" >4615729</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col4\" class=\"data row22 col4\" >328724</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col5\" class=\"data row22 col5\" >7.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col0\" class=\"data row23 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col1\" class=\"data row23 col1\" >23</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col2\" class=\"data row23 col2\" >4217228</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col3\" class=\"data row23 col3\" >4702156</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col4\" class=\"data row23 col4\" >484928</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col5\" class=\"data row23 col5\" >11.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col0\" class=\"data row24 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col1\" class=\"data row24 col1\" >24</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col2\" class=\"data row24 col2\" >4243602</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col3\" class=\"data row24 col3\" >4695411</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col4\" class=\"data row24 col4\" >451809</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col5\" class=\"data row24 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col0\" class=\"data row25 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col1\" class=\"data row25 col1\" >25</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col2\" class=\"data row25 col2\" >4289428</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col3\" class=\"data row25 col3\" >4511370</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col4\" class=\"data row25 col4\" >221942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col5\" class=\"data row25 col5\" >5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col0\" class=\"data row26 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col1\" class=\"data row26 col1\" >26</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col2\" class=\"data row26 col2\" >4160806</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col3\" class=\"data row26 col3\" >4408043</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col4\" class=\"data row26 col4\" >247237</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col5\" class=\"data row26 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col0\" class=\"data row27 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col1\" class=\"data row27 col1\" >27</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col2\" class=\"data row27 col2\" >4237026</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col3\" class=\"data row27 col3\" >4334806</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col4\" class=\"data row27 col4\" >97780</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col5\" class=\"data row27 col5\" >2.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col0\" class=\"data row28 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col1\" class=\"data row28 col1\" >28</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col2\" class=\"data row28 col2\" >4247541</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col3\" class=\"data row28 col3\" >4355240</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col4\" class=\"data row28 col4\" >107699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col5\" class=\"data row28 col5\" >2.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col0\" class=\"data row29 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col1\" class=\"data row29 col1\" >29</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col2\" class=\"data row29 col2\" >4210286</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col3\" class=\"data row29 col3\" >4391788</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col4\" class=\"data row29 col4\" >181502</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col5\" class=\"data row29 col5\" >4.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col0\" class=\"data row30 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col1\" class=\"data row30 col1\" >30</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col2\" class=\"data row30 col2\" >4304239</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col3\" class=\"data row30 col3\" >4255334</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col4\" class=\"data row30 col4\" >-48905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col5\" class=\"data row30 col5\" >-1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col0\" class=\"data row31 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col1\" class=\"data row31 col1\" >31</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col2\" class=\"data row31 col2\" >4042516</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col3\" class=\"data row31 col3\" >4323217</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col4\" class=\"data row31 col4\" >280701</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col5\" class=\"data row31 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col0\" class=\"data row32 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col1\" class=\"data row32 col1\" >32</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col2\" class=\"data row32 col2\" >3967602</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col3\" class=\"data row32 col3\" >4323951</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col4\" class=\"data row32 col4\" >356349</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col5\" class=\"data row32 col5\" >8.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col0\" class=\"data row33 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col1\" class=\"data row33 col1\" >33</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col2\" class=\"data row33 col2\" >3933581</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col3\" class=\"data row33 col3\" >4278664</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col4\" class=\"data row33 col4\" >345083</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col5\" class=\"data row33 col5\" >8.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col0\" class=\"data row34 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col1\" class=\"data row34 col1\" >34</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col2\" class=\"data row34 col2\" >3822189</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col3\" class=\"data row34 col3\" >4364748</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col4\" class=\"data row34 col4\" >542559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col5\" class=\"data row34 col5\" >14.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col0\" class=\"data row35 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col1\" class=\"data row35 col1\" >35</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col2\" class=\"data row35 col2\" >3948335</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col3\" class=\"data row35 col3\" >4095782</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col4\" class=\"data row35 col4\" >147447</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col5\" class=\"data row35 col5\" >3.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col0\" class=\"data row36 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col1\" class=\"data row36 col1\" >36</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col2\" class=\"data row36 col2\" >3830199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col3\" class=\"data row36 col3\" >4016711</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col4\" class=\"data row36 col4\" >186512</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col5\" class=\"data row36 col5\" >4.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col0\" class=\"data row37 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col1\" class=\"data row37 col1\" >37</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col2\" class=\"data row37 col2\" >3896766</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col3\" class=\"data row37 col3\" >3976750</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col4\" class=\"data row37 col4\" >79984</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col5\" class=\"data row37 col5\" >2.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col0\" class=\"data row38 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col1\" class=\"data row38 col1\" >38</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col2\" class=\"data row38 col2\" >4080228</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col3\" class=\"data row38 col3\" >3861636</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col4\" class=\"data row38 col4\" >-218592</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col5\" class=\"data row38 col5\" >-5.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col0\" class=\"data row39 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col1\" class=\"data row39 col1\" >39</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col2\" class=\"data row39 col2\" >4324463</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col3\" class=\"data row39 col3\" >3982507</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col4\" class=\"data row39 col4\" >-341956</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col5\" class=\"data row39 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col0\" class=\"data row40 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col1\" class=\"data row40 col1\" >40</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col2\" class=\"data row40 col2\" >4387480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col3\" class=\"data row40 col3\" >3859395</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col4\" class=\"data row40 col4\" >-528085</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col5\" class=\"data row40 col5\" >-12.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col0\" class=\"data row41 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col1\" class=\"data row41 col1\" >41</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col2\" class=\"data row41 col2\" >4163478</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col3\" class=\"data row41 col3\" >3919810</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col4\" class=\"data row41 col4\" >-243668</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col5\" class=\"data row41 col5\" >-5.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col0\" class=\"data row42 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col1\" class=\"data row42 col1\" >42</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col2\" class=\"data row42 col2\" >4082712</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col3\" class=\"data row42 col3\" >4097698</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col4\" class=\"data row42 col4\" >14986</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col5\" class=\"data row42 col5\" >0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col0\" class=\"data row43 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col1\" class=\"data row43 col1\" >43</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col2\" class=\"data row43 col2\" >4093844</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col3\" class=\"data row43 col3\" >4333850</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col4\" class=\"data row43 col4\" >240006</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col5\" class=\"data row43 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col0\" class=\"data row44 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col1\" class=\"data row44 col1\" >44</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col2\" class=\"data row44 col2\" >4178508</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col3\" class=\"data row44 col3\" >4390283</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col4\" class=\"data row44 col4\" >211775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col5\" class=\"data row44 col5\" >5.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col0\" class=\"data row45 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col1\" class=\"data row45 col1\" >45</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col2\" class=\"data row45 col2\" >4438559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col3\" class=\"data row45 col3\" >4162629</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col4\" class=\"data row45 col4\" >-275930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col5\" class=\"data row45 col5\" >-6.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col0\" class=\"data row46 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col1\" class=\"data row46 col1\" >46</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col2\" class=\"data row46 col2\" >4529716</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col3\" class=\"data row46 col3\" >4077151</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col4\" class=\"data row46 col4\" >-452565</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col5\" class=\"data row46 col5\" >-9.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col0\" class=\"data row47 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col1\" class=\"data row47 col1\" >47</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col2\" class=\"data row47 col2\" >4535473</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col3\" class=\"data row47 col3\" >4082883</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col4\" class=\"data row47 col4\" >-452590</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col5\" class=\"data row47 col5\" >-9.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col0\" class=\"data row48 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col1\" class=\"data row48 col1\" >48</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col2\" class=\"data row48 col2\" >4534663</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col3\" class=\"data row48 col3\" >4159738</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col4\" class=\"data row48 col4\" >-374925</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col5\" class=\"data row48 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col0\" class=\"data row49 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col1\" class=\"data row49 col1\" >49</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col2\" class=\"data row49 col2\" >4599098</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col3\" class=\"data row49 col3\" >4410246</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col4\" class=\"data row49 col4\" >-188852</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col5\" class=\"data row49 col5\" >-4.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col0\" class=\"data row50 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col1\" class=\"data row50 col1\" >50</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col2\" class=\"data row50 col2\" >4646231</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col3\" class=\"data row50 col3\" >4492407</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col4\" class=\"data row50 col4\" >-153824</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col5\" class=\"data row50 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col0\" class=\"data row51 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col1\" class=\"data row51 col1\" >51</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col2\" class=\"data row51 col2\" >4498974</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col3\" class=\"data row51 col3\" >4489393</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col4\" class=\"data row51 col4\" >-9581</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col5\" class=\"data row51 col5\" >-0.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col0\" class=\"data row52 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col1\" class=\"data row52 col1\" >52</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col2\" class=\"data row52 col2\" >4480584</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col3\" class=\"data row52 col3\" >4480188</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col4\" class=\"data row52 col4\" >-396</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col5\" class=\"data row52 col5\" >-0.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col0\" class=\"data row53 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col1\" class=\"data row53 col1\" >53</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col2\" class=\"data row53 col2\" >4439403</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col3\" class=\"data row53 col3\" >4535430</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col4\" class=\"data row53 col4\" >96027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col5\" class=\"data row53 col5\" >2.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col0\" class=\"data row54 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col1\" class=\"data row54 col1\" >54</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col2\" class=\"data row54 col2\" >4288447</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col3\" class=\"data row54 col3\" >4574760</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col4\" class=\"data row54 col4\" >286313</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col5\" class=\"data row54 col5\" >6.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col0\" class=\"data row55 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col1\" class=\"data row55 col1\" >55</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col2\" class=\"data row55 col2\" >4258970</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col3\" class=\"data row55 col3\" >4421856</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col4\" class=\"data row55 col4\" >162886</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col5\" class=\"data row55 col5\" >3.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col0\" class=\"data row56 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col1\" class=\"data row56 col1\" >56</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col2\" class=\"data row56 col2\" >4093136</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col3\" class=\"data row56 col3\" >4395949</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col4\" class=\"data row56 col4\" >302813</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col5\" class=\"data row56 col5\" >7.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col0\" class=\"data row57 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col1\" class=\"data row57 col1\" >57</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col2\" class=\"data row57 col2\" >3946518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col3\" class=\"data row57 col3\" >4347023</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col4\" class=\"data row57 col4\" >400505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col5\" class=\"data row57 col5\" >10.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col0\" class=\"data row58 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col1\" class=\"data row58 col1\" >58</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col2\" class=\"data row58 col2\" >3802447</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col3\" class=\"data row58 col3\" >4191360</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col4\" class=\"data row58 col4\" >388913</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col5\" class=\"data row58 col5\" >10.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col0\" class=\"data row59 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col1\" class=\"data row59 col1\" >59</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col2\" class=\"data row59 col2\" >3694254</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col3\" class=\"data row59 col3\" >4155521</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col4\" class=\"data row59 col4\" >461267</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col5\" class=\"data row59 col5\" >12.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col0\" class=\"data row60 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col1\" class=\"data row60 col1\" >60</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col2\" class=\"data row60 col2\" >3616721</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col3\" class=\"data row60 col3\" >3985598</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col4\" class=\"data row60 col4\" >368877</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col5\" class=\"data row60 col5\" >10.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col0\" class=\"data row61 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col1\" class=\"data row61 col1\" >61</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col2\" class=\"data row61 col2\" >3520109</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col3\" class=\"data row61 col3\" >3834367</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col4\" class=\"data row61 col4\" >314258</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col5\" class=\"data row61 col5\" >8.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col0\" class=\"data row62 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col1\" class=\"data row62 col1\" >62</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col2\" class=\"data row62 col2\" >3495059</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col3\" class=\"data row62 col3\" >3685282</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col4\" class=\"data row62 col4\" >190223</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col5\" class=\"data row62 col5\" >5.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col0\" class=\"data row63 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col1\" class=\"data row63 col1\" >63</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col2\" class=\"data row63 col2\" >3652167</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col3\" class=\"data row63 col3\" >3571610</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col4\" class=\"data row63 col4\" >-80557</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col5\" class=\"data row63 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col0\" class=\"data row64 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col1\" class=\"data row64 col1\" >64</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col2\" class=\"data row64 col2\" >2706055</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col3\" class=\"data row64 col3\" >3487559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col4\" class=\"data row64 col4\" >781504</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col5\" class=\"data row64 col5\" >28.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col0\" class=\"data row65 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col1\" class=\"data row65 col1\" >65</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col2\" class=\"data row65 col2\" >2678525</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col3\" class=\"data row65 col3\" >3382824</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col4\" class=\"data row65 col4\" >704299</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col5\" class=\"data row65 col5\" >26.29%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col0\" class=\"data row66 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col1\" class=\"data row66 col1\" >66</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col2\" class=\"data row66 col2\" >2621335</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col3\" class=\"data row66 col3\" >3347060</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col4\" class=\"data row66 col4\" >725725</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col5\" class=\"data row66 col5\" >27.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col0\" class=\"data row67 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col1\" class=\"data row67 col1\" >67</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col2\" class=\"data row67 col2\" >2693707</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col3\" class=\"data row67 col3\" >3485241</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col4\" class=\"data row67 col4\" >791534</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col5\" class=\"data row67 col5\" >29.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col0\" class=\"data row68 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col1\" class=\"data row68 col1\" >68</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col2\" class=\"data row68 col2\" >2359816</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col3\" class=\"data row68 col3\" >2572359</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col4\" class=\"data row68 col4\" >212543</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col5\" class=\"data row68 col5\" >9.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col0\" class=\"data row69 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col1\" class=\"data row69 col1\" >69</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col2\" class=\"data row69 col2\" >2167830</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col3\" class=\"data row69 col3\" >2534295</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col4\" class=\"data row69 col4\" >366465</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col5\" class=\"data row69 col5\" >16.90%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col0\" class=\"data row70 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col1\" class=\"data row70 col1\" >70</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col2\" class=\"data row70 col2\" >2062577</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col3\" class=\"data row70 col3\" >2465438</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col4\" class=\"data row70 col4\" >402861</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col5\" class=\"data row70 col5\" >19.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col0\" class=\"data row71 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col1\" class=\"data row71 col1\" >71</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col2\" class=\"data row71 col2\" >1953607</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col3\" class=\"data row71 col3\" >2519705</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col4\" class=\"data row71 col4\" >566098</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col5\" class=\"data row71 col5\" >28.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col0\" class=\"data row72 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col1\" class=\"data row72 col1\" >72</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col2\" class=\"data row72 col2\" >1883820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col3\" class=\"data row72 col3\" >2193945</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col4\" class=\"data row72 col4\" >310125</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col5\" class=\"data row72 col5\" >16.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col0\" class=\"data row73 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col1\" class=\"data row73 col1\" >73</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col2\" class=\"data row73 col2\" >1750304</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col3\" class=\"data row73 col3\" >2001700</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col4\" class=\"data row73 col4\" >251396</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col5\" class=\"data row73 col5\" >14.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col0\" class=\"data row74 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col1\" class=\"data row74 col1\" >74</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col2\" class=\"data row74 col2\" >1685995</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col3\" class=\"data row74 col3\" >1889513</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col4\" class=\"data row74 col4\" >203518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col5\" class=\"data row74 col5\" >12.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col0\" class=\"data row75 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col1\" class=\"data row75 col1\" >75</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col2\" class=\"data row75 col2\" >1631878</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col3\" class=\"data row75 col3\" >1773756</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col4\" class=\"data row75 col4\" >141878</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col5\" class=\"data row75 col5\" >8.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col0\" class=\"data row76 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col1\" class=\"data row76 col1\" >76</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col2\" class=\"data row76 col2\" >1481680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col3\" class=\"data row76 col3\" >1693674</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col4\" class=\"data row76 col4\" >211994</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col5\" class=\"data row76 col5\" >14.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col0\" class=\"data row77 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col1\" class=\"data row77 col1\" >77</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col2\" class=\"data row77 col2\" >1449173</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col3\" class=\"data row77 col3\" >1556104</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col4\" class=\"data row77 col4\" >106931</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col5\" class=\"data row77 col5\" >7.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col0\" class=\"data row78 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col1\" class=\"data row78 col1\" >78</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col2\" class=\"data row78 col2\" >1402182</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col3\" class=\"data row78 col3\" >1480611</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col4\" class=\"data row78 col4\" >78429</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col5\" class=\"data row78 col5\" >5.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col0\" class=\"data row79 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col1\" class=\"data row79 col1\" >79</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col2\" class=\"data row79 col2\" >1354912</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col3\" class=\"data row79 col3\" >1413193</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col4\" class=\"data row79 col4\" >58281</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col5\" class=\"data row79 col5\" >4.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col0\" class=\"data row80 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col1\" class=\"data row80 col1\" >80</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col2\" class=\"data row80 col2\" >1319725</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col3\" class=\"data row80 col3\" >1262537</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col4\" class=\"data row80 col4\" >-57188</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col5\" class=\"data row80 col5\" >-4.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row81\" class=\"row_heading level0 row81\" >81</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col0\" class=\"data row81 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col1\" class=\"data row81 col1\" >81</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col2\" class=\"data row81 col2\" >1212603</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col3\" class=\"data row81 col3\" >1214357</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col4\" class=\"data row81 col4\" >1754</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col5\" class=\"data row81 col5\" >0.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row82\" class=\"row_heading level0 row82\" >82</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col0\" class=\"data row82 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col1\" class=\"data row82 col1\" >82</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col2\" class=\"data row82 col2\" >1158351</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col3\" class=\"data row82 col3\" >1151677</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col4\" class=\"data row82 col4\" >-6674</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col5\" class=\"data row82 col5\" >-0.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row83\" class=\"row_heading level0 row83\" >83</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col0\" class=\"data row83 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col1\" class=\"data row83 col1\" >83</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col2\" class=\"data row83 col2\" >1081440</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col3\" class=\"data row83 col3\" >1088601</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col4\" class=\"data row83 col4\" >7161</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col5\" class=\"data row83 col5\" >0.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row84\" class=\"row_heading level0 row84\" >84</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col0\" class=\"data row84 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col1\" class=\"data row84 col1\" >84</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col2\" class=\"data row84 col2\" >987023</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col3\" class=\"data row84 col3\" >1034369</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col4\" class=\"data row84 col4\" >47346</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col5\" class=\"data row84 col5\" >4.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row85\" class=\"row_heading level0 row85\" >85</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col0\" class=\"data row85 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col1\" class=\"data row85 col1\" >85</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col2\" class=\"data row85 col2\" >915013</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col3\" class=\"data row85 col3\" >922947</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col4\" class=\"data row85 col4\" >7934</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col5\" class=\"data row85 col5\" >0.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row86\" class=\"row_heading level0 row86\" >86</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col0\" class=\"data row86 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col1\" class=\"data row86 col1\" >86</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col2\" class=\"data row86 col2\" >821549</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col3\" class=\"data row86 col3\" >853723</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col4\" class=\"data row86 col4\" >32174</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col5\" class=\"data row86 col5\" >3.92%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row87\" class=\"row_heading level0 row87\" >87</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col0\" class=\"data row87 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col1\" class=\"data row87 col1\" >87</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col2\" class=\"data row87 col2\" >721196</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col3\" class=\"data row87 col3\" >768676</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col4\" class=\"data row87 col4\" >47480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col5\" class=\"data row87 col5\" >6.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row88\" class=\"row_heading level0 row88\" >88</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col0\" class=\"data row88 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col1\" class=\"data row88 col1\" >88</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col2\" class=\"data row88 col2\" >636657</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col3\" class=\"data row88 col3\" >673402</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col4\" class=\"data row88 col4\" >36745</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col5\" class=\"data row88 col5\" >5.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row89\" class=\"row_heading level0 row89\" >89</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col0\" class=\"data row89 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col1\" class=\"data row89 col1\" >89</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col2\" class=\"data row89 col2\" >546193</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col3\" class=\"data row89 col3\" >597828</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col4\" class=\"data row89 col4\" >51635</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col5\" class=\"data row89 col5\" >9.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row90\" class=\"row_heading level0 row90\" >90</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col0\" class=\"data row90 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col1\" class=\"data row90 col1\" >90</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col2\" class=\"data row90 col2\" >448324</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col3\" class=\"data row90 col3\" >511074</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col4\" class=\"data row90 col4\" >62750</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col5\" class=\"data row90 col5\" >14.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row91\" class=\"row_heading level0 row91\" >91</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col0\" class=\"data row91 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col1\" class=\"data row91 col1\" >91</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col2\" class=\"data row91 col2\" >344442</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col3\" class=\"data row91 col3\" >425314</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col4\" class=\"data row91 col4\" >80872</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col5\" class=\"data row91 col5\" >23.48%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row92\" class=\"row_heading level0 row92\" >92</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col0\" class=\"data row92 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col1\" class=\"data row92 col1\" >92</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col2\" class=\"data row92 col2\" >288841</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col3\" class=\"data row92 col3\" >352912</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col4\" class=\"data row92 col4\" >64071</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col5\" class=\"data row92 col5\" >22.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row93\" class=\"row_heading level0 row93\" >93</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col0\" class=\"data row93 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col1\" class=\"data row93 col1\" >93</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col2\" class=\"data row93 col2\" >219064</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col3\" class=\"data row93 col3\" >284885</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col4\" class=\"data row93 col4\" >65821</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col5\" class=\"data row93 col5\" >30.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row94\" class=\"row_heading level0 row94\" >94</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col0\" class=\"data row94 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col1\" class=\"data row94 col1\" >94</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col2\" class=\"data row94 col2\" >170775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col3\" class=\"data row94 col3\" >217328</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col4\" class=\"data row94 col4\" >46553</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col5\" class=\"data row94 col5\" >27.26%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row95\" class=\"row_heading level0 row95\" >95</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col0\" class=\"data row95 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col1\" class=\"data row95 col1\" >95</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col2\" class=\"data row95 col2\" >131077</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col3\" class=\"data row95 col3\" >156288</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col4\" class=\"data row95 col4\" >25211</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col5\" class=\"data row95 col5\" >19.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row96\" class=\"row_heading level0 row96\" >96</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col0\" class=\"data row96 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col1\" class=\"data row96 col1\" >96</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col2\" class=\"data row96 col2\" >97161</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col3\" class=\"data row96 col3\" >120485</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col4\" class=\"data row96 col4\" >23324</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col5\" class=\"data row96 col5\" >24.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row97\" class=\"row_heading level0 row97\" >97</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col0\" class=\"data row97 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col1\" class=\"data row97 col1\" >97</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col2\" class=\"data row97 col2\" >68893</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col3\" class=\"data row97 col3\" >83089</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col4\" class=\"data row97 col4\" >14196</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col5\" class=\"data row97 col5\" >20.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row98\" class=\"row_heading level0 row98\" >98</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col0\" class=\"data row98 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col1\" class=\"data row98 col1\" >98</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col2\" class=\"data row98 col2\" >47037</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col3\" class=\"data row98 col3\" >59726</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col4\" class=\"data row98 col4\" >12689</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col5\" class=\"data row98 col5\" >26.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row99\" class=\"row_heading level0 row99\" >99</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col0\" class=\"data row99 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col1\" class=\"data row99 col1\" >99</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col2\" class=\"data row99 col2\" >32178</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col3\" class=\"data row99 col3\" >41468</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col4\" class=\"data row99 col4\" >9290</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col5\" class=\"data row99 col5\" >28.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row100\" class=\"row_heading level0 row100\" >100</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col0\" class=\"data row100 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col1\" class=\"data row100 col1\" >100</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col2\" class=\"data row100 col2\" >54410</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col3\" class=\"data row100 col3\" >71626</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col4\" class=\"data row100 col4\" >17216</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col5\" class=\"data row100 col5\" >31.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row101\" class=\"row_heading level0 row101\" >101</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col0\" class=\"data row101 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col1\" class=\"data row101 col1\" >999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col2\" class=\"data row101 col2\" >309346863</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col3\" class=\"data row101 col3\" >318907401</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col4\" class=\"data row101 col4\" >9560538</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col5\" class=\"data row101 col5\" >3.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row102\" class=\"row_heading level0 row102\" >102</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col0\" class=\"data row102 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col1\" class=\"data row102 col1\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col2\" class=\"data row102 col2\" >2018420</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col3\" class=\"data row102 col3\" >2020326</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col4\" class=\"data row102 col4\" >1906</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col5\" class=\"data row102 col5\" >0.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row103\" class=\"row_heading level0 row103\" >103</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col0\" class=\"data row103 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col1\" class=\"data row103 col1\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col2\" class=\"data row103 col2\" >2020332</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col3\" class=\"data row103 col3\" >2018401</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col4\" class=\"data row103 col4\" >-1931</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col5\" class=\"data row103 col5\" >-0.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row104\" class=\"row_heading level0 row104\" >104</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col0\" class=\"data row104 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col1\" class=\"data row104 col1\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col2\" class=\"data row104 col2\" >2088685</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col3\" class=\"data row104 col3\" >2023673</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col4\" class=\"data row104 col4\" >-65012</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col5\" class=\"data row104 col5\" >-3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row105\" class=\"row_heading level0 row105\" >105</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col0\" class=\"data row105 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col1\" class=\"data row105 col1\" >3</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col2\" class=\"data row105 col2\" >2101272</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col3\" class=\"data row105 col3\" >2049596</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col4\" class=\"data row105 col4\" >-51676</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col5\" class=\"data row105 col5\" >-2.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row106\" class=\"row_heading level0 row106\" >106</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col0\" class=\"data row106 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col1\" class=\"data row106 col1\" >4</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col2\" class=\"data row106 col2\" >2084312</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col3\" class=\"data row106 col3\" >2044517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col4\" class=\"data row106 col4\" >-39795</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col5\" class=\"data row106 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row107\" class=\"row_heading level0 row107\" >107</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col0\" class=\"data row107 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col1\" class=\"data row107 col1\" >5</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col2\" class=\"data row107 col2\" >2076573</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col3\" class=\"data row107 col3\" >2044339</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col4\" class=\"data row107 col4\" >-32234</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col5\" class=\"data row107 col5\" >-1.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row108\" class=\"row_heading level0 row108\" >108</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col0\" class=\"data row108 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col1\" class=\"data row108 col1\" >6</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col2\" class=\"data row108 col2\" >2079410</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col3\" class=\"data row108 col3\" >2111060</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col4\" class=\"data row108 col4\" >31650</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col5\" class=\"data row108 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row109\" class=\"row_heading level0 row109\" >109</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col0\" class=\"data row109 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col1\" class=\"data row109 col1\" >7</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col2\" class=\"data row109 col2\" >2063139</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col3\" class=\"data row109 col3\" >2122832</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col4\" class=\"data row109 col4\" >59693</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col5\" class=\"data row109 col5\" >2.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row110\" class=\"row_heading level0 row110\" >110</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col0\" class=\"data row110 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col1\" class=\"data row110 col1\" >8</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col2\" class=\"data row110 col2\" >2054462</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col3\" class=\"data row110 col3\" >2105618</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col4\" class=\"data row110 col4\" >51156</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col5\" class=\"data row110 col5\" >2.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row111\" class=\"row_heading level0 row111\" >111</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col0\" class=\"data row111 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col1\" class=\"data row111 col1\" >9</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col2\" class=\"data row111 col2\" >2107037</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col3\" class=\"data row111 col3\" >2097690</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col4\" class=\"data row111 col4\" >-9347</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col5\" class=\"data row111 col5\" >-0.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row112\" class=\"row_heading level0 row112\" >112</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col0\" class=\"data row112 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col1\" class=\"data row112 col1\" >10</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col2\" class=\"data row112 col2\" >2142167</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col3\" class=\"data row112 col3\" >2100262</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col4\" class=\"data row112 col4\" >-41905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col5\" class=\"data row112 col5\" >-1.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row113\" class=\"row_heading level0 row113\" >113</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col0\" class=\"data row113 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col1\" class=\"data row113 col1\" >11</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col2\" class=\"data row113 col2\" >2104797</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col3\" class=\"data row113 col3\" >2084169</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col4\" class=\"data row113 col4\" >-20628</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col5\" class=\"data row113 col5\" >-0.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row114\" class=\"row_heading level0 row114\" >114</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col0\" class=\"data row114 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col1\" class=\"data row114 col1\" >12</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col2\" class=\"data row114 col2\" >2103649</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col3\" class=\"data row114 col3\" >2075836</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col4\" class=\"data row114 col4\" >-27813</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col5\" class=\"data row114 col5\" >-1.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row115\" class=\"row_heading level0 row115\" >115</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col0\" class=\"data row115 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col1\" class=\"data row115 col1\" >13</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col2\" class=\"data row115 col2\" >2104949</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col3\" class=\"data row115 col3\" >2128914</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col4\" class=\"data row115 col4\" >23965</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col5\" class=\"data row115 col5\" >1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row116\" class=\"row_heading level0 row116\" >116</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col0\" class=\"data row116 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col1\" class=\"data row116 col1\" >14</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col2\" class=\"data row116 col2\" >2122913</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col3\" class=\"data row116 col3\" >2164924</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col4\" class=\"data row116 col4\" >42011</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col5\" class=\"data row116 col5\" >1.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row117\" class=\"row_heading level0 row117\" >117</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col0\" class=\"data row117 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col1\" class=\"data row117 col1\" >15</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col2\" class=\"data row117 col2\" >2170442</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col3\" class=\"data row117 col3\" >2129062</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col4\" class=\"data row117 col4\" >-41380</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col5\" class=\"data row117 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row118\" class=\"row_heading level0 row118\" >118</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col0\" class=\"data row118 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col1\" class=\"data row118 col1\" >16</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col2\" class=\"data row118 col2\" >2215032</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col3\" class=\"data row118 col3\" >2131425</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col4\" class=\"data row118 col4\" >-83607</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col5\" class=\"data row118 col5\" >-3.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row119\" class=\"row_heading level0 row119\" >119</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col0\" class=\"data row119 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col1\" class=\"data row119 col1\" >17</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col2\" class=\"data row119 col2\" >2252838</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col3\" class=\"data row119 col3\" >2139361</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col4\" class=\"data row119 col4\" >-113477</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col5\" class=\"data row119 col5\" >-5.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row120\" class=\"row_heading level0 row120\" >120</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col0\" class=\"data row120 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col1\" class=\"data row120 col1\" >18</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col2\" class=\"data row120 col2\" >2305733</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col3\" class=\"data row120 col3\" >2165744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col4\" class=\"data row120 col4\" >-139989</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col5\" class=\"data row120 col5\" >-6.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row121\" class=\"row_heading level0 row121\" >121</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col0\" class=\"data row121 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col1\" class=\"data row121 col1\" >19</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col2\" class=\"data row121 col2\" >2334906</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col3\" class=\"data row121 col3\" >2221910</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col4\" class=\"data row121 col4\" >-112996</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col5\" class=\"data row121 col5\" >-4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row122\" class=\"row_heading level0 row122\" >122</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col0\" class=\"data row122 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col1\" class=\"data row122 col1\" >20</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col2\" class=\"data row122 col2\" >2331845</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col3\" class=\"data row122 col3\" >2271216</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col4\" class=\"data row122 col4\" >-60629</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col5\" class=\"data row122 col5\" >-2.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row123\" class=\"row_heading level0 row123\" >123</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col0\" class=\"data row123 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col1\" class=\"data row123 col1\" >21</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col2\" class=\"data row123 col2\" >2241083</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col3\" class=\"data row123 col3\" >2312917</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col4\" class=\"data row123 col4\" >71834</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col5\" class=\"data row123 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row124\" class=\"row_heading level0 row124\" >124</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col0\" class=\"data row124 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col1\" class=\"data row124 col1\" >22</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col2\" class=\"data row124 col2\" >2188199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col3\" class=\"data row124 col3\" >2370459</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col4\" class=\"data row124 col4\" >182260</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col5\" class=\"data row124 col5\" >8.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row125\" class=\"row_heading level0 row125\" >125</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col0\" class=\"data row125 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col1\" class=\"data row125 col1\" >23</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col2\" class=\"data row125 col2\" >2151068</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col3\" class=\"data row125 col3\" >2402294</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col4\" class=\"data row125 col4\" >251226</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col5\" class=\"data row125 col5\" >11.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row126\" class=\"row_heading level0 row126\" >126</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col0\" class=\"data row126 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col1\" class=\"data row126 col1\" >24</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col2\" class=\"data row126 col2\" >2161347</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col3\" class=\"data row126 col3\" >2393037</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col4\" class=\"data row126 col4\" >231690</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col5\" class=\"data row126 col5\" >10.72%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row127\" class=\"row_heading level0 row127\" >127</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col0\" class=\"data row127 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col1\" class=\"data row127 col1\" >25</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col2\" class=\"data row127 col2\" >2177131</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col3\" class=\"data row127 col3\" >2296875</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col4\" class=\"data row127 col4\" >119744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col5\" class=\"data row127 col5\" >5.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row128\" class=\"row_heading level0 row128\" >128</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col0\" class=\"data row128 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col1\" class=\"data row128 col1\" >26</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col2\" class=\"data row128 col2\" >2102331</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col3\" class=\"data row128 col3\" >2240881</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col4\" class=\"data row128 col4\" >138550</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col5\" class=\"data row128 col5\" >6.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row129\" class=\"row_heading level0 row129\" >129</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col0\" class=\"data row129 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col1\" class=\"data row129 col1\" >27</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col2\" class=\"data row129 col2\" >2135178</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col3\" class=\"data row129 col3\" >2201518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col4\" class=\"data row129 col4\" >66340</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col5\" class=\"data row129 col5\" >3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row130\" class=\"row_heading level0 row130\" >130</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col0\" class=\"data row130 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col1\" class=\"data row130 col1\" >28</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col2\" class=\"data row130 col2\" >2134981</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col3\" class=\"data row130 col3\" >2208749</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col4\" class=\"data row130 col4\" >73768</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col5\" class=\"data row130 col5\" >3.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row131\" class=\"row_heading level0 row131\" >131</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col0\" class=\"data row131 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col1\" class=\"data row131 col1\" >29</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col2\" class=\"data row131 col2\" >2112313</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col3\" class=\"data row131 col3\" >2219872</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col4\" class=\"data row131 col4\" >107559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col5\" class=\"data row131 col5\" >5.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row132\" class=\"row_heading level0 row132\" >132</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col0\" class=\"data row132 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col1\" class=\"data row132 col1\" >30</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col2\" class=\"data row132 col2\" >2167495</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col3\" class=\"data row132 col3\" >2142240</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col4\" class=\"data row132 col4\" >-25255</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col5\" class=\"data row132 col5\" >-1.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row133\" class=\"row_heading level0 row133\" >133</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col0\" class=\"data row133 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col1\" class=\"data row133 col1\" >31</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col2\" class=\"data row133 col2\" >2026439</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col3\" class=\"data row133 col3\" >2171839</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col4\" class=\"data row133 col4\" >145400</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col5\" class=\"data row133 col5\" >7.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row134\" class=\"row_heading level0 row134\" >134</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col0\" class=\"data row134 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col1\" class=\"data row134 col1\" >32</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col2\" class=\"data row134 col2\" >1986147</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col3\" class=\"data row134 col3\" >2167557</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col4\" class=\"data row134 col4\" >181410</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col5\" class=\"data row134 col5\" >9.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row135\" class=\"row_heading level0 row135\" >135</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col0\" class=\"data row135 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col1\" class=\"data row135 col1\" >33</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col2\" class=\"data row135 col2\" >1963645</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col3\" class=\"data row135 col3\" >2141552</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col4\" class=\"data row135 col4\" >177907</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col5\" class=\"data row135 col5\" >9.06%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row136\" class=\"row_heading level0 row136\" >136</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col0\" class=\"data row136 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col1\" class=\"data row136 col1\" >34</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col2\" class=\"data row136 col2\" >1908731</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col3\" class=\"data row136 col3\" >2192877</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col4\" class=\"data row136 col4\" >284146</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col5\" class=\"data row136 col5\" >14.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row137\" class=\"row_heading level0 row137\" >137</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col0\" class=\"data row137 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col1\" class=\"data row137 col1\" >35</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col2\" class=\"data row137 col2\" >1974636</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col3\" class=\"data row137 col3\" >2047877</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col4\" class=\"data row137 col4\" >73241</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col5\" class=\"data row137 col5\" >3.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row138\" class=\"row_heading level0 row138\" >138</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col0\" class=\"data row138 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col1\" class=\"data row138 col1\" >36</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col2\" class=\"data row138 col2\" >1907408</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col3\" class=\"data row138 col3\" >2005880</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col4\" class=\"data row138 col4\" >98472</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col5\" class=\"data row138 col5\" >5.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row139\" class=\"row_heading level0 row139\" >139</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col0\" class=\"data row139 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col1\" class=\"data row139 col1\" >37</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col2\" class=\"data row139 col2\" >1934537</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col3\" class=\"data row139 col3\" >1979888</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col4\" class=\"data row139 col4\" >45351</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col5\" class=\"data row139 col5\" >2.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row140\" class=\"row_heading level0 row140\" >140</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col0\" class=\"data row140 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col1\" class=\"data row140 col1\" >38</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col2\" class=\"data row140 col2\" >2028052</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col3\" class=\"data row140 col3\" >1923133</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col4\" class=\"data row140 col4\" >-104919</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col5\" class=\"data row140 col5\" >-5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row141\" class=\"row_heading level0 row141\" >141</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col0\" class=\"data row141 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col1\" class=\"data row141 col1\" >39</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col2\" class=\"data row141 col2\" >2148718</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col3\" class=\"data row141 col3\" >1986712</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col4\" class=\"data row141 col4\" >-162006</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col5\" class=\"data row141 col5\" >-7.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row142\" class=\"row_heading level0 row142\" >142</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col0\" class=\"data row142 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col1\" class=\"data row142 col1\" >40</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col2\" class=\"data row142 col2\" >2189516</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col3\" class=\"data row142 col3\" >1917201</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col4\" class=\"data row142 col4\" >-272315</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col5\" class=\"data row142 col5\" >-12.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row143\" class=\"row_heading level0 row143\" >143</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col0\" class=\"data row143 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col1\" class=\"data row143 col1\" >41</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col2\" class=\"data row143 col2\" >2073902</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col3\" class=\"data row143 col3\" >1941203</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col4\" class=\"data row143 col4\" >-132699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col5\" class=\"data row143 col5\" >-6.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row144\" class=\"row_heading level0 row144\" >144</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col0\" class=\"data row144 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col1\" class=\"data row144 col1\" >42</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col2\" class=\"data row144 col2\" >2031782</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col3\" class=\"data row144 col3\" >2032207</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col4\" class=\"data row144 col4\" >425</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col5\" class=\"data row144 col5\" >0.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row145\" class=\"row_heading level0 row145\" >145</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col0\" class=\"data row145 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col1\" class=\"data row145 col1\" >43</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col2\" class=\"data row145 col2\" >2030982</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col3\" class=\"data row145 col3\" >2147960</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col4\" class=\"data row145 col4\" >116978</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col5\" class=\"data row145 col5\" >5.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row146\" class=\"row_heading level0 row146\" >146</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col0\" class=\"data row146 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col1\" class=\"data row146 col1\" >44</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col2\" class=\"data row146 col2\" >2074572</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col3\" class=\"data row146 col3\" >2184448</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col4\" class=\"data row146 col4\" >109876</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col5\" class=\"data row146 col5\" >5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row147\" class=\"row_heading level0 row147\" >147</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col0\" class=\"data row147 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col1\" class=\"data row147 col1\" >45</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col2\" class=\"data row147 col2\" >2201905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col3\" class=\"data row147 col3\" >2067426</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col4\" class=\"data row147 col4\" >-134479</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col5\" class=\"data row147 col5\" >-6.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row148\" class=\"row_heading level0 row148\" >148</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col0\" class=\"data row148 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col1\" class=\"data row148 col1\" >46</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col2\" class=\"data row148 col2\" >2238774</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col3\" class=\"data row148 col3\" >2023033</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col4\" class=\"data row148 col4\" >-215741</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col5\" class=\"data row148 col5\" >-9.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row149\" class=\"row_heading level0 row149\" >149</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col0\" class=\"data row149 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col1\" class=\"data row149 col1\" >47</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col2\" class=\"data row149 col2\" >2237940</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col3\" class=\"data row149 col3\" >2019517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col4\" class=\"data row149 col4\" >-218423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col5\" class=\"data row149 col5\" >-9.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row150\" class=\"row_heading level0 row150\" >150</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col0\" class=\"data row150 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col1\" class=\"data row150 col1\" >48</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col2\" class=\"data row150 col2\" >2235296</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col3\" class=\"data row150 col3\" >2058392</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col4\" class=\"data row150 col4\" >-176904</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col5\" class=\"data row150 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row151\" class=\"row_heading level0 row151\" >151</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col0\" class=\"data row151 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col1\" class=\"data row151 col1\" >49</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col2\" class=\"data row151 col2\" >2262458</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col3\" class=\"data row151 col3\" >2180214</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col4\" class=\"data row151 col4\" >-82244</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col5\" class=\"data row151 col5\" >-3.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row152\" class=\"row_heading level0 row152\" >152</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col0\" class=\"data row152 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col1\" class=\"data row152 col1\" >50</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col2\" class=\"data row152 col2\" >2290862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col3\" class=\"data row152 col3\" >2211767</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col4\" class=\"data row152 col4\" >-79095</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col5\" class=\"data row152 col5\" >-3.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row153\" class=\"row_heading level0 row153\" >153</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col0\" class=\"data row153 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col1\" class=\"data row153 col1\" >51</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col2\" class=\"data row153 col2\" >2209780</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col3\" class=\"data row153 col3\" >2205399</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col4\" class=\"data row153 col4\" >-4381</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col5\" class=\"data row153 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row154\" class=\"row_heading level0 row154\" >154</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col0\" class=\"data row154 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col1\" class=\"data row154 col1\" >52</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col2\" class=\"data row154 col2\" >2197161</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col3\" class=\"data row154 col3\" >2197801</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col4\" class=\"data row154 col4\" >640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col5\" class=\"data row154 col5\" >0.03%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row155\" class=\"row_heading level0 row155\" >155</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col0\" class=\"data row155 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col1\" class=\"data row155 col1\" >53</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col2\" class=\"data row155 col2\" >2170923</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col3\" class=\"data row155 col3\" >2219328</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col4\" class=\"data row155 col4\" >48405</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col5\" class=\"data row155 col5\" >2.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row156\" class=\"row_heading level0 row156\" >156</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col0\" class=\"data row156 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col1\" class=\"data row156 col1\" >54</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col2\" class=\"data row156 col2\" >2091640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col3\" class=\"data row156 col3\" >2242757</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col4\" class=\"data row156 col4\" >151117</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col5\" class=\"data row156 col5\" >7.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row157\" class=\"row_heading level0 row157\" >157</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col0\" class=\"data row157 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col1\" class=\"data row157 col1\" >55</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col2\" class=\"data row157 col2\" >2075199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col3\" class=\"data row157 col3\" >2158427</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col4\" class=\"data row157 col4\" >83228</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col5\" class=\"data row157 col5\" >4.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row158\" class=\"row_heading level0 row158\" >158</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col0\" class=\"data row158 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col1\" class=\"data row158 col1\" >56</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col2\" class=\"data row158 col2\" >1984452</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col3\" class=\"data row158 col3\" >2140940</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col4\" class=\"data row158 col4\" >156488</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col5\" class=\"data row158 col5\" >7.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row159\" class=\"row_heading level0 row159\" >159</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col0\" class=\"data row159 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col1\" class=\"data row159 col1\" >57</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col2\" class=\"data row159 col2\" >1909997</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col3\" class=\"data row159 col3\" >2109804</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col4\" class=\"data row159 col4\" >199807</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col5\" class=\"data row159 col5\" >10.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row160\" class=\"row_heading level0 row160\" >160</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col0\" class=\"data row160 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col1\" class=\"data row160 col1\" >58</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col2\" class=\"data row160 col2\" >1838680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col3\" class=\"data row160 col3\" >2027452</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col4\" class=\"data row160 col4\" >188772</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col5\" class=\"data row160 col5\" >10.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row161\" class=\"row_heading level0 row161\" >161</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col0\" class=\"data row161 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col1\" class=\"data row161 col1\" >59</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col2\" class=\"data row161 col2\" >1779480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col3\" class=\"data row161 col3\" >2006587</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col4\" class=\"data row161 col4\" >227107</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col5\" class=\"data row161 col5\" >12.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row162\" class=\"row_heading level0 row162\" >162</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col0\" class=\"data row162 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col1\" class=\"data row162 col1\" >60</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col2\" class=\"data row162 col2\" >1742220</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col3\" class=\"data row162 col3\" >1913729</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col4\" class=\"data row162 col4\" >171509</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col5\" class=\"data row162 col5\" >9.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row163\" class=\"row_heading level0 row163\" >163</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col0\" class=\"data row163 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col1\" class=\"data row163 col1\" >61</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col2\" class=\"data row163 col2\" >1691401</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col3\" class=\"data row163 col3\" >1836656</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col4\" class=\"data row163 col4\" >145255</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col5\" class=\"data row163 col5\" >8.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row164\" class=\"row_heading level0 row164\" >164</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col0\" class=\"data row164 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col1\" class=\"data row164 col1\" >62</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col2\" class=\"data row164 col2\" >1679060</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col3\" class=\"data row164 col3\" >1762880</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col4\" class=\"data row164 col4\" >83820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col5\" class=\"data row164 col5\" >4.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row165\" class=\"row_heading level0 row165\" >165</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col0\" class=\"data row165 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col1\" class=\"data row165 col1\" >63</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col2\" class=\"data row165 col2\" >1753903</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col3\" class=\"data row165 col3\" >1701014</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col4\" class=\"data row165 col4\" >-52889</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col5\" class=\"data row165 col5\" >-3.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row166\" class=\"row_heading level0 row166\" >166</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col0\" class=\"data row166 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col1\" class=\"data row166 col1\" >64</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col2\" class=\"data row166 col2\" >1291833</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col3\" class=\"data row166 col3\" >1660815</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col4\" class=\"data row166 col4\" >368982</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col5\" class=\"data row166 col5\" >28.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row167\" class=\"row_heading level0 row167\" >167</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col0\" class=\"data row167 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col1\" class=\"data row167 col1\" >65</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col2\" class=\"data row167 col2\" >1272686</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col3\" class=\"data row167 col3\" >1606772</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col4\" class=\"data row167 col4\" >334086</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col5\" class=\"data row167 col5\" >26.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row168\" class=\"row_heading level0 row168\" >168</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col0\" class=\"data row168 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col1\" class=\"data row168 col1\" >66</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col2\" class=\"data row168 col2\" >1239794</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col3\" class=\"data row168 col3\" >1588723</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col4\" class=\"data row168 col4\" >348929</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col5\" class=\"data row168 col5\" >28.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row169\" class=\"row_heading level0 row169\" >169</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col0\" class=\"data row169 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col1\" class=\"data row169 col1\" >67</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col2\" class=\"data row169 col2\" >1270145</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col3\" class=\"data row169 col3\" >1652998</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col4\" class=\"data row169 col4\" >382853</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col5\" class=\"data row169 col5\" >30.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row170\" class=\"row_heading level0 row170\" >170</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col0\" class=\"data row170 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col1\" class=\"data row170 col1\" >68</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col2\" class=\"data row170 col2\" >1105699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col3\" class=\"data row170 col3\" >1211278</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col4\" class=\"data row170 col4\" >105579</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col5\" class=\"data row170 col5\" >9.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row171\" class=\"row_heading level0 row171\" >171</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col0\" class=\"data row171 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col1\" class=\"data row171 col1\" >69</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col2\" class=\"data row171 col2\" >1006782</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col3\" class=\"data row171 col3\" >1186872</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col4\" class=\"data row171 col4\" >180090</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col5\" class=\"data row171 col5\" >17.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row172\" class=\"row_heading level0 row172\" >172</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col0\" class=\"data row172 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col1\" class=\"data row172 col1\" >70</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col2\" class=\"data row172 col2\" >954073</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col3\" class=\"data row172 col3\" >1148508</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col4\" class=\"data row172 col4\" >194435</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col5\" class=\"data row172 col5\" >20.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row173\" class=\"row_heading level0 row173\" >173</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col0\" class=\"data row173 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col1\" class=\"data row173 col1\" >71</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col2\" class=\"data row173 col2\" >903258</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col3\" class=\"data row173 col3\" >1169115</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col4\" class=\"data row173 col4\" >265857</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col5\" class=\"data row173 col5\" >29.43%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row174\" class=\"row_heading level0 row174\" >174</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col0\" class=\"data row174 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col1\" class=\"data row174 col1\" >72</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col2\" class=\"data row174 col2\" >862529</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col3\" class=\"data row174 col3\" >1010582</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col4\" class=\"data row174 col4\" >148053</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col5\" class=\"data row174 col5\" >17.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row175\" class=\"row_heading level0 row175\" >175</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col0\" class=\"data row175 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col1\" class=\"data row175 col1\" >73</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col2\" class=\"data row175 col2\" >794646</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col3\" class=\"data row175 col3\" >912673</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col4\" class=\"data row175 col4\" >118027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col5\" class=\"data row175 col5\" >14.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row176\" class=\"row_heading level0 row176\" >176</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col0\" class=\"data row176 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col1\" class=\"data row176 col1\" >74</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col2\" class=\"data row176 col2\" >758830</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col3\" class=\"data row176 col3\" >856970</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col4\" class=\"data row176 col4\" >98140</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col5\" class=\"data row176 col5\" >12.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row177\" class=\"row_heading level0 row177\" >177</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col0\" class=\"data row177 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col1\" class=\"data row177 col1\" >75</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col2\" class=\"data row177 col2\" >725663</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col3\" class=\"data row177 col3\" >802960</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col4\" class=\"data row177 col4\" >77297</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col5\" class=\"data row177 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row178\" class=\"row_heading level0 row178\" >178</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col0\" class=\"data row178 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col1\" class=\"data row178 col1\" >76</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col2\" class=\"data row178 col2\" >653551</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col3\" class=\"data row178 col3\" >757841</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col4\" class=\"data row178 col4\" >104290</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col5\" class=\"data row178 col5\" >15.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row179\" class=\"row_heading level0 row179\" >179</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col0\" class=\"data row179 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col1\" class=\"data row179 col1\" >77</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col2\" class=\"data row179 col2\" >630867</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col3\" class=\"data row179 col3\" >689162</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col4\" class=\"data row179 col4\" >58295</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col5\" class=\"data row179 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row180\" class=\"row_heading level0 row180\" >180</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col0\" class=\"data row180 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col1\" class=\"data row180 col1\" >78</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col2\" class=\"data row180 col2\" >602774</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col3\" class=\"data row180 col3\" >648696</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col4\" class=\"data row180 col4\" >45922</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col5\" class=\"data row180 col5\" >7.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row181\" class=\"row_heading level0 row181\" >181</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col0\" class=\"data row181 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col1\" class=\"data row181 col1\" >79</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col2\" class=\"data row181 col2\" >573885</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col3\" class=\"data row181 col3\" >610115</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col4\" class=\"data row181 col4\" >36230</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col5\" class=\"data row181 col5\" >6.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row182\" class=\"row_heading level0 row182\" >182</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col0\" class=\"data row182 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col1\" class=\"data row182 col1\" >80</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col2\" class=\"data row182 col2\" >549216</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col3\" class=\"data row182 col3\" >539227</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col4\" class=\"data row182 col4\" >-9989</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col5\" class=\"data row182 col5\" >-1.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row183\" class=\"row_heading level0 row183\" >183</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col0\" class=\"data row183 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col1\" class=\"data row183 col1\" >81</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col2\" class=\"data row183 col2\" >496070</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col3\" class=\"data row183 col3\" >510305</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col4\" class=\"data row183 col4\" >14235</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col5\" class=\"data row183 col5\" >2.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row184\" class=\"row_heading level0 row184\" >184</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col0\" class=\"data row184 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col1\" class=\"data row184 col1\" >82</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col2\" class=\"data row184 col2\" >462807</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col3\" class=\"data row184 col3\" >476034</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col4\" class=\"data row184 col4\" >13227</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col5\" class=\"data row184 col5\" >2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row185\" class=\"row_heading level0 row185\" >185</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col0\" class=\"data row185 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col1\" class=\"data row185 col1\" >83</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col2\" class=\"data row185 col2\" >422999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col3\" class=\"data row185 col3\" >441530</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col4\" class=\"data row185 col4\" >18531</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col5\" class=\"data row185 col5\" >4.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row186\" class=\"row_heading level0 row186\" >186</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col0\" class=\"data row186 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col1\" class=\"data row186 col1\" >84</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col2\" class=\"data row186 col2\" >375685</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col3\" class=\"data row186 col3\" >410385</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col4\" class=\"data row186 col4\" >34700</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col5\" class=\"data row186 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row187\" class=\"row_heading level0 row187\" >187</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col0\" class=\"data row187 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col1\" class=\"data row187 col1\" >85</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col2\" class=\"data row187 col2\" >337661</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col3\" class=\"data row187 col3\" >358342</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col4\" class=\"data row187 col4\" >20681</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col5\" class=\"data row187 col5\" >6.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row188\" class=\"row_heading level0 row188\" >188</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col0\" class=\"data row188 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col1\" class=\"data row188 col1\" >86</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col2\" class=\"data row188 col2\" >295396</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col3\" class=\"data row188 col3\" >322043</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col4\" class=\"data row188 col4\" >26647</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col5\" class=\"data row188 col5\" >9.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row189\" class=\"row_heading level0 row189\" >189</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col0\" class=\"data row189 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col1\" class=\"data row189 col1\" >87</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col2\" class=\"data row189 col2\" >253621</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col3\" class=\"data row189 col3\" >282423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col4\" class=\"data row189 col4\" >28802</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col5\" class=\"data row189 col5\" >11.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row190\" class=\"row_heading level0 row190\" >190</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col0\" class=\"data row190 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col1\" class=\"data row190 col1\" >88</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col2\" class=\"data row190 col2\" >216220</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col3\" class=\"data row190 col3\" >239455</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col4\" class=\"data row190 col4\" >23235</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col5\" class=\"data row190 col5\" >10.75%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row191\" class=\"row_heading level0 row191\" >191</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col0\" class=\"data row191 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col1\" class=\"data row191 col1\" >89</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col2\" class=\"data row191 col2\" >180461</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col3\" class=\"data row191 col3\" >204850</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col4\" class=\"data row191 col4\" >24389</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col5\" class=\"data row191 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row192\" class=\"row_heading level0 row192\" >192</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col0\" class=\"data row192 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col1\" class=\"data row192 col1\" >90</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col2\" class=\"data row192 col2\" >141399</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col3\" class=\"data row192 col3\" >169644</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col4\" class=\"data row192 col4\" >28245</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col5\" class=\"data row192 col5\" >19.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row193\" class=\"row_heading level0 row193\" >193</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col0\" class=\"data row193 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col1\" class=\"data row193 col1\" >91</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col2\" class=\"data row193 col2\" >104291</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col3\" class=\"data row193 col3\" >137425</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col4\" class=\"data row193 col4\" >33134</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col5\" class=\"data row193 col5\" >31.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row194\" class=\"row_heading level0 row194\" >194</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col0\" class=\"data row194 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col1\" class=\"data row194 col1\" >92</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col2\" class=\"data row194 col2\" >83462</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col3\" class=\"data row194 col3\" >109264</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col4\" class=\"data row194 col4\" >25802</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col5\" class=\"data row194 col5\" >30.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row195\" class=\"row_heading level0 row195\" >195</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col0\" class=\"data row195 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col1\" class=\"data row195 col1\" >93</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col2\" class=\"data row195 col2\" >60182</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col3\" class=\"data row195 col3\" >85459</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col4\" class=\"data row195 col4\" >25277</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col5\" class=\"data row195 col5\" >42.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row196\" class=\"row_heading level0 row196\" >196</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col0\" class=\"data row196 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col1\" class=\"data row196 col1\" >94</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col2\" class=\"data row196 col2\" >43827</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col3\" class=\"data row196 col3\" >61691</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col4\" class=\"data row196 col4\" >17864</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col5\" class=\"data row196 col5\" >40.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row197\" class=\"row_heading level0 row197\" >197</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col0\" class=\"data row197 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col1\" class=\"data row197 col1\" >95</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col2\" class=\"data row197 col2\" >31736</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col3\" class=\"data row197 col3\" >42556</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col4\" class=\"data row197 col4\" >10820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col5\" class=\"data row197 col5\" >34.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row198\" class=\"row_heading level0 row198\" >198</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col0\" class=\"data row198 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col1\" class=\"data row198 col1\" >96</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col2\" class=\"data row198 col2\" >22022</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col3\" class=\"data row198 col3\" >31053</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col4\" class=\"data row198 col4\" >9031</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col5\" class=\"data row198 col5\" >41.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row199\" class=\"row_heading level0 row199\" >199</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col0\" class=\"data row199 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col1\" class=\"data row199 col1\" >97</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col2\" class=\"data row199 col2\" >14775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col3\" class=\"data row199 col3\" >20310</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col4\" class=\"data row199 col4\" >5535</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col5\" class=\"data row199 col5\" >37.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row200\" class=\"row_heading level0 row200\" >200</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col0\" class=\"data row200 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col1\" class=\"data row200 col1\" >98</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col2\" class=\"data row200 col2\" >9505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col3\" class=\"data row200 col3\" >13518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col4\" class=\"data row200 col4\" >4013</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col5\" class=\"data row200 col5\" >42.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row201\" class=\"row_heading level0 row201\" >201</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col0\" class=\"data row201 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col1\" class=\"data row201 col1\" >99</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col2\" class=\"data row201 col2\" >6104</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col3\" class=\"data row201 col3\" >8951</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col4\" class=\"data row201 col4\" >2847</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col5\" class=\"data row201 col5\" >46.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row202\" class=\"row_heading level0 row202\" >202</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col0\" class=\"data row202 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col1\" class=\"data row202 col1\" >100</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col2\" class=\"data row202 col2\" >9352</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col3\" class=\"data row202 col3\" >13618</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col4\" class=\"data row202 col4\" >4266</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col5\" class=\"data row202 col5\" >45.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row203\" class=\"row_heading level0 row203\" >203</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col0\" class=\"data row203 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col1\" class=\"data row203 col1\" >999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col2\" class=\"data row203 col2\" >152088043</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col3\" class=\"data row203 col3\" >156955337</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col4\" class=\"data row203 col4\" >4867294</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col5\" class=\"data row203 col5\" >3.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row204\" class=\"row_heading level0 row204\" >204</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col0\" class=\"data row204 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col1\" class=\"data row204 col1\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col2\" class=\"data row204 col2\" >1932910</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col3\" class=\"data row204 col3\" >1929449</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col4\" class=\"data row204 col4\" >-3461</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col5\" class=\"data row204 col5\" >-0.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row205\" class=\"row_heading level0 row205\" >205</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col0\" class=\"data row205 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col1\" class=\"data row205 col1\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col2\" class=\"data row205 col2\" >1937556</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col3\" class=\"data row205 col3\" >1931375</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col4\" class=\"data row205 col4\" >-6181</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col5\" class=\"data row205 col5\" >-0.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row206\" class=\"row_heading level0 row206\" >206</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col0\" class=\"data row206 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col1\" class=\"data row206 col1\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col2\" class=\"data row206 col2\" >2002177</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col3\" class=\"data row206 col3\" >1935991</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col4\" class=\"data row206 col4\" >-66186</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col5\" class=\"data row206 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row207\" class=\"row_heading level0 row207\" >207</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col0\" class=\"data row207 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col1\" class=\"data row207 col1\" >3</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col2\" class=\"data row207 col2\" >2010648</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col3\" class=\"data row207 col3\" >1957483</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col4\" class=\"data row207 col4\" >-53165</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col5\" class=\"data row207 col5\" >-2.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row208\" class=\"row_heading level0 row208\" >208</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col0\" class=\"data row208 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col1\" class=\"data row208 col1\" >4</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col2\" class=\"data row208 col2\" >1993239</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col3\" class=\"data row208 col3\" >1961199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col4\" class=\"data row208 col4\" >-32040</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col5\" class=\"data row208 col5\" >-1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row209\" class=\"row_heading level0 row209\" >209</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col0\" class=\"data row209 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col1\" class=\"data row209 col1\" >5</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col2\" class=\"data row209 col2\" >1988080</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col3\" class=\"data row209 col3\" >1962561</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col4\" class=\"data row209 col4\" >-25519</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col5\" class=\"data row209 col5\" >-1.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row210\" class=\"row_heading level0 row210\" >210</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col0\" class=\"data row210 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col1\" class=\"data row210 col1\" >6</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col2\" class=\"data row210 col2\" >1993603</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col3\" class=\"data row210 col3\" >2024870</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col4\" class=\"data row210 col4\" >31267</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col5\" class=\"data row210 col5\" >1.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row211\" class=\"row_heading level0 row211\" >211</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col0\" class=\"data row211 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col1\" class=\"data row211 col1\" >7</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col2\" class=\"data row211 col2\" >1979907</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col3\" class=\"data row211 col3\" >2032494</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col4\" class=\"data row211 col4\" >52587</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col5\" class=\"data row211 col5\" >2.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row212\" class=\"row_heading level0 row212\" >212</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col0\" class=\"data row212 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col1\" class=\"data row212 col1\" >8</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col2\" class=\"data row212 col2\" >1971142</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col3\" class=\"data row212 col3\" >2015285</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col4\" class=\"data row212 col4\" >44143</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col5\" class=\"data row212 col5\" >2.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row213\" class=\"row_heading level0 row213\" >213</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col0\" class=\"data row213 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col1\" class=\"data row213 col1\" >9</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col2\" class=\"data row213 col2\" >2018378</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col3\" class=\"data row213 col3\" >2010659</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col4\" class=\"data row213 col4\" >-7719</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col5\" class=\"data row213 col5\" >-0.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row214\" class=\"row_heading level0 row214\" >214</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col0\" class=\"data row214 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col1\" class=\"data row214 col1\" >10</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col2\" class=\"data row214 col2\" >2044895</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col3\" class=\"data row214 col3\" >2016680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col4\" class=\"data row214 col4\" >-28215</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col5\" class=\"data row214 col5\" >-1.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row215\" class=\"row_heading level0 row215\" >215</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col0\" class=\"data row215 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col1\" class=\"data row215 col1\" >11</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col2\" class=\"data row215 col2\" >2010714</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col3\" class=\"data row215 col3\" >2003233</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col4\" class=\"data row215 col4\" >-7481</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col5\" class=\"data row215 col5\" >-0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row216\" class=\"row_heading level0 row216\" >216</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col0\" class=\"data row216 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col1\" class=\"data row216 col1\" >12</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col2\" class=\"data row216 col2\" >2009630</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col3\" class=\"data row216 col3\" >1994846</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col4\" class=\"data row216 col4\" >-14784</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col5\" class=\"data row216 col5\" >-0.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row217\" class=\"row_heading level0 row217\" >217</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col0\" class=\"data row217 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col1\" class=\"data row217 col1\" >13</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col2\" class=\"data row217 col2\" >2014717</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col3\" class=\"data row217 col3\" >2042116</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col4\" class=\"data row217 col4\" >27399</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col5\" class=\"data row217 col5\" >1.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row218\" class=\"row_heading level0 row218\" >218</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col0\" class=\"data row218 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col1\" class=\"data row218 col1\" >14</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col2\" class=\"data row218 col2\" >2022701</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col3\" class=\"data row218 col3\" >2068915</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col4\" class=\"data row218 col4\" >46214</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col5\" class=\"data row218 col5\" >2.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row219\" class=\"row_heading level0 row219\" >219</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col0\" class=\"data row219 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col1\" class=\"data row219 col1\" >15</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col2\" class=\"data row219 col2\" >2060560</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col3\" class=\"data row219 col3\" >2035734</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col4\" class=\"data row219 col4\" >-24826</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col5\" class=\"data row219 col5\" >-1.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row220\" class=\"row_heading level0 row220\" >220</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col0\" class=\"data row220 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col1\" class=\"data row220 col1\" >16</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col2\" class=\"data row220 col2\" >2098220</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col3\" class=\"data row220 col3\" >2037134</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col4\" class=\"data row220 col4\" >-61086</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col5\" class=\"data row220 col5\" >-2.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row221\" class=\"row_heading level0 row221\" >221</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col0\" class=\"data row221 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col1\" class=\"data row221 col1\" >17</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col2\" class=\"data row221 col2\" >2123529</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col3\" class=\"data row221 col3\" >2047152</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col4\" class=\"data row221 col4\" >-76377</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col5\" class=\"data row221 col5\" >-3.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row222\" class=\"row_heading level0 row222\" >222</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col0\" class=\"data row222 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col1\" class=\"data row222 col1\" >18</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col2\" class=\"data row222 col2\" >2185272</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col3\" class=\"data row222 col3\" >2062176</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col4\" class=\"data row222 col4\" >-123096</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col5\" class=\"data row222 col5\" >-5.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row223\" class=\"row_heading level0 row223\" >223</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col0\" class=\"data row223 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col1\" class=\"data row223 col1\" >19</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col2\" class=\"data row223 col2\" >2236505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col3\" class=\"data row223 col3\" >2107128</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col4\" class=\"data row223 col4\" >-129377</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col5\" class=\"data row223 col5\" >-5.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row224\" class=\"row_heading level0 row224\" >224</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col0\" class=\"data row224 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col1\" class=\"data row224 col1\" >20</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col2\" class=\"data row224 col2\" >2236672</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col3\" class=\"data row224 col3\" >2150114</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col4\" class=\"data row224 col4\" >-86558</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col5\" class=\"data row224 col5\" >-3.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row225\" class=\"row_heading level0 row225\" >225</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col0\" class=\"data row225 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col1\" class=\"data row225 col1\" >21</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col2\" class=\"data row225 col2\" >2146873</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col3\" class=\"data row225 col3\" >2179456</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col4\" class=\"data row225 col4\" >32583</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col5\" class=\"data row225 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row226\" class=\"row_heading level0 row226\" >226</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col0\" class=\"data row226 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col1\" class=\"data row226 col1\" >22</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col2\" class=\"data row226 col2\" >2098806</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col3\" class=\"data row226 col3\" >2245270</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col4\" class=\"data row226 col4\" >146464</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col5\" class=\"data row226 col5\" >6.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row227\" class=\"row_heading level0 row227\" >227</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col0\" class=\"data row227 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col1\" class=\"data row227 col1\" >23</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col2\" class=\"data row227 col2\" >2066160</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col3\" class=\"data row227 col3\" >2299862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col4\" class=\"data row227 col4\" >233702</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col5\" class=\"data row227 col5\" >11.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row228\" class=\"row_heading level0 row228\" >228</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col0\" class=\"data row228 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col1\" class=\"data row228 col1\" >24</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col2\" class=\"data row228 col2\" >2082255</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col3\" class=\"data row228 col3\" >2302374</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col4\" class=\"data row228 col4\" >220119</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col5\" class=\"data row228 col5\" >10.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row229\" class=\"row_heading level0 row229\" >229</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col0\" class=\"data row229 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col1\" class=\"data row229 col1\" >25</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col2\" class=\"data row229 col2\" >2112297</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col3\" class=\"data row229 col3\" >2214495</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col4\" class=\"data row229 col4\" >102198</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col5\" class=\"data row229 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row230\" class=\"row_heading level0 row230\" >230</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col0\" class=\"data row230 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col1\" class=\"data row230 col1\" >26</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col2\" class=\"data row230 col2\" >2058475</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col3\" class=\"data row230 col3\" >2167162</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col4\" class=\"data row230 col4\" >108687</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col5\" class=\"data row230 col5\" >5.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row231\" class=\"row_heading level0 row231\" >231</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col0\" class=\"data row231 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col1\" class=\"data row231 col1\" >27</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col2\" class=\"data row231 col2\" >2101848</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col3\" class=\"data row231 col3\" >2133288</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col4\" class=\"data row231 col4\" >31440</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col5\" class=\"data row231 col5\" >1.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row232\" class=\"row_heading level0 row232\" >232</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col0\" class=\"data row232 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col1\" class=\"data row232 col1\" >28</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col2\" class=\"data row232 col2\" >2112560</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col3\" class=\"data row232 col3\" >2146491</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col4\" class=\"data row232 col4\" >33931</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col5\" class=\"data row232 col5\" >1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row233\" class=\"row_heading level0 row233\" >233</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col0\" class=\"data row233 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col1\" class=\"data row233 col1\" >29</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col2\" class=\"data row233 col2\" >2097973</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col3\" class=\"data row233 col3\" >2171916</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col4\" class=\"data row233 col4\" >73943</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col5\" class=\"data row233 col5\" >3.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row234\" class=\"row_heading level0 row234\" >234</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col0\" class=\"data row234 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col1\" class=\"data row234 col1\" >30</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col2\" class=\"data row234 col2\" >2136744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col3\" class=\"data row234 col3\" >2113094</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col4\" class=\"data row234 col4\" >-23650</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col5\" class=\"data row234 col5\" >-1.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row235\" class=\"row_heading level0 row235\" >235</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col0\" class=\"data row235 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col1\" class=\"data row235 col1\" >31</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col2\" class=\"data row235 col2\" >2016077</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col3\" class=\"data row235 col3\" >2151378</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col4\" class=\"data row235 col4\" >135301</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col5\" class=\"data row235 col5\" >6.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row236\" class=\"row_heading level0 row236\" >236</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col0\" class=\"data row236 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col1\" class=\"data row236 col1\" >32</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col2\" class=\"data row236 col2\" >1981455</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col3\" class=\"data row236 col3\" >2156394</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col4\" class=\"data row236 col4\" >174939</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col5\" class=\"data row236 col5\" >8.83%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row237\" class=\"row_heading level0 row237\" >237</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col0\" class=\"data row237 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col1\" class=\"data row237 col1\" >33</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col2\" class=\"data row237 col2\" >1969936</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col3\" class=\"data row237 col3\" >2137112</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col4\" class=\"data row237 col4\" >167176</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col5\" class=\"data row237 col5\" >8.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row238\" class=\"row_heading level0 row238\" >238</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col0\" class=\"data row238 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col1\" class=\"data row238 col1\" >34</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col2\" class=\"data row238 col2\" >1913458</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col3\" class=\"data row238 col3\" >2171871</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col4\" class=\"data row238 col4\" >258413</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col5\" class=\"data row238 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row239\" class=\"row_heading level0 row239\" >239</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col0\" class=\"data row239 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col1\" class=\"data row239 col1\" >35</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col2\" class=\"data row239 col2\" >1973699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col3\" class=\"data row239 col3\" >2047905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col4\" class=\"data row239 col4\" >74206</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col5\" class=\"data row239 col5\" >3.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row240\" class=\"row_heading level0 row240\" >240</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col0\" class=\"data row240 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col1\" class=\"data row240 col1\" >36</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col2\" class=\"data row240 col2\" >1922791</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col3\" class=\"data row240 col3\" >2010831</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col4\" class=\"data row240 col4\" >88040</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col5\" class=\"data row240 col5\" >4.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row241\" class=\"row_heading level0 row241\" >241</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col0\" class=\"data row241 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col1\" class=\"data row241 col1\" >37</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col2\" class=\"data row241 col2\" >1962229</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col3\" class=\"data row241 col3\" >1996862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col4\" class=\"data row241 col4\" >34633</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col5\" class=\"data row241 col5\" >1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row242\" class=\"row_heading level0 row242\" >242</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col0\" class=\"data row242 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col1\" class=\"data row242 col1\" >38</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col2\" class=\"data row242 col2\" >2052176</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col3\" class=\"data row242 col3\" >1938503</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col4\" class=\"data row242 col4\" >-113673</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col5\" class=\"data row242 col5\" >-5.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row243\" class=\"row_heading level0 row243\" >243</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col0\" class=\"data row243 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col1\" class=\"data row243 col1\" >39</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col2\" class=\"data row243 col2\" >2175745</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col3\" class=\"data row243 col3\" >1995795</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col4\" class=\"data row243 col4\" >-179950</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col5\" class=\"data row243 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row244\" class=\"row_heading level0 row244\" >244</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col0\" class=\"data row244 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col1\" class=\"data row244 col1\" >40</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col2\" class=\"data row244 col2\" >2197964</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col3\" class=\"data row244 col3\" >1942194</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col4\" class=\"data row244 col4\" >-255770</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col5\" class=\"data row244 col5\" >-11.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row245\" class=\"row_heading level0 row245\" >245</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col0\" class=\"data row245 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col1\" class=\"data row245 col1\" >41</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col2\" class=\"data row245 col2\" >2089576</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col3\" class=\"data row245 col3\" >1978607</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col4\" class=\"data row245 col4\" >-110969</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col5\" class=\"data row245 col5\" >-5.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row246\" class=\"row_heading level0 row246\" >246</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col0\" class=\"data row246 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col1\" class=\"data row246 col1\" >42</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col2\" class=\"data row246 col2\" >2050930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col3\" class=\"data row246 col3\" >2065491</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col4\" class=\"data row246 col4\" >14561</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col5\" class=\"data row246 col5\" >0.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row247\" class=\"row_heading level0 row247\" >247</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col0\" class=\"data row247 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col1\" class=\"data row247 col1\" >43</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col2\" class=\"data row247 col2\" >2062862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col3\" class=\"data row247 col3\" >2185890</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col4\" class=\"data row247 col4\" >123028</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col5\" class=\"data row247 col5\" >5.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row248\" class=\"row_heading level0 row248\" >248</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col0\" class=\"data row248 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col1\" class=\"data row248 col1\" >44</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col2\" class=\"data row248 col2\" >2103936</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col3\" class=\"data row248 col3\" >2205835</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col4\" class=\"data row248 col4\" >101899</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col5\" class=\"data row248 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row249\" class=\"row_heading level0 row249\" >249</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col0\" class=\"data row249 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col1\" class=\"data row249 col1\" >45</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col2\" class=\"data row249 col2\" >2236654</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col3\" class=\"data row249 col3\" >2095203</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col4\" class=\"data row249 col4\" >-141451</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col5\" class=\"data row249 col5\" >-6.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row250\" class=\"row_heading level0 row250\" >250</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col0\" class=\"data row250 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col1\" class=\"data row250 col1\" >46</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col2\" class=\"data row250 col2\" >2290942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col3\" class=\"data row250 col3\" >2054118</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col4\" class=\"data row250 col4\" >-236824</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col5\" class=\"data row250 col5\" >-10.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row251\" class=\"row_heading level0 row251\" >251</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col0\" class=\"data row251 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col1\" class=\"data row251 col1\" >47</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col2\" class=\"data row251 col2\" >2297533</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col3\" class=\"data row251 col3\" >2063366</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col4\" class=\"data row251 col4\" >-234167</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col5\" class=\"data row251 col5\" >-10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row252\" class=\"row_heading level0 row252\" >252</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col0\" class=\"data row252 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col1\" class=\"data row252 col1\" >48</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col2\" class=\"data row252 col2\" >2299367</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col3\" class=\"data row252 col3\" >2101346</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col4\" class=\"data row252 col4\" >-198021</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col5\" class=\"data row252 col5\" >-8.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row253\" class=\"row_heading level0 row253\" >253</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col0\" class=\"data row253 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col1\" class=\"data row253 col1\" >49</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col2\" class=\"data row253 col2\" >2336640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col3\" class=\"data row253 col3\" >2230032</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col4\" class=\"data row253 col4\" >-106608</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col5\" class=\"data row253 col5\" >-4.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row254\" class=\"row_heading level0 row254\" >254</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col0\" class=\"data row254 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col1\" class=\"data row254 col1\" >50</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col2\" class=\"data row254 col2\" >2355369</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col3\" class=\"data row254 col3\" >2280640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col4\" class=\"data row254 col4\" >-74729</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col5\" class=\"data row254 col5\" >-3.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row255\" class=\"row_heading level0 row255\" >255</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col0\" class=\"data row255 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col1\" class=\"data row255 col1\" >51</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col2\" class=\"data row255 col2\" >2289194</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col3\" class=\"data row255 col3\" >2283994</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col4\" class=\"data row255 col4\" >-5200</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col5\" class=\"data row255 col5\" >-0.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row256\" class=\"row_heading level0 row256\" >256</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col0\" class=\"data row256 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col1\" class=\"data row256 col1\" >52</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col2\" class=\"data row256 col2\" >2283423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col3\" class=\"data row256 col3\" >2282387</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col4\" class=\"data row256 col4\" >-1036</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col5\" class=\"data row256 col5\" >-0.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row257\" class=\"row_heading level0 row257\" >257</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col0\" class=\"data row257 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col1\" class=\"data row257 col1\" >53</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col2\" class=\"data row257 col2\" >2268480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col3\" class=\"data row257 col3\" >2316102</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col4\" class=\"data row257 col4\" >47622</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col5\" class=\"data row257 col5\" >2.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row258\" class=\"row_heading level0 row258\" >258</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col0\" class=\"data row258 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col1\" class=\"data row258 col1\" >54</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col2\" class=\"data row258 col2\" >2196807</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col3\" class=\"data row258 col3\" >2332003</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col4\" class=\"data row258 col4\" >135196</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col5\" class=\"data row258 col5\" >6.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row259\" class=\"row_heading level0 row259\" >259</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col0\" class=\"data row259 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col1\" class=\"data row259 col1\" >55</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col2\" class=\"data row259 col2\" >2183771</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col3\" class=\"data row259 col3\" >2263429</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col4\" class=\"data row259 col4\" >79658</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col5\" class=\"data row259 col5\" >3.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row260\" class=\"row_heading level0 row260\" >260</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col0\" class=\"data row260 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col1\" class=\"data row260 col1\" >56</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col2\" class=\"data row260 col2\" >2108684</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col3\" class=\"data row260 col3\" >2255009</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col4\" class=\"data row260 col4\" >146325</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col5\" class=\"data row260 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row261\" class=\"row_heading level0 row261\" >261</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col0\" class=\"data row261 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col1\" class=\"data row261 col1\" >57</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col2\" class=\"data row261 col2\" >2036521</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col3\" class=\"data row261 col3\" >2237219</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col4\" class=\"data row261 col4\" >200698</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col5\" class=\"data row261 col5\" >9.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row262\" class=\"row_heading level0 row262\" >262</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col0\" class=\"data row262 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col1\" class=\"data row262 col1\" >58</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col2\" class=\"data row262 col2\" >1963767</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col3\" class=\"data row262 col3\" >2163908</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col4\" class=\"data row262 col4\" >200141</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col5\" class=\"data row262 col5\" >10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row263\" class=\"row_heading level0 row263\" >263</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col0\" class=\"data row263 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col1\" class=\"data row263 col1\" >59</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col2\" class=\"data row263 col2\" >1914774</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col3\" class=\"data row263 col3\" >2148934</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col4\" class=\"data row263 col4\" >234160</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col5\" class=\"data row263 col5\" >12.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row264\" class=\"row_heading level0 row264\" >264</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col0\" class=\"data row264 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col1\" class=\"data row264 col1\" >60</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col2\" class=\"data row264 col2\" >1874501</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col3\" class=\"data row264 col3\" >2071869</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col4\" class=\"data row264 col4\" >197368</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col5\" class=\"data row264 col5\" >10.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row265\" class=\"row_heading level0 row265\" >265</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col0\" class=\"data row265 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col1\" class=\"data row265 col1\" >61</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col2\" class=\"data row265 col2\" >1828708</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col3\" class=\"data row265 col3\" >1997711</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col4\" class=\"data row265 col4\" >169003</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col5\" class=\"data row265 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row266\" class=\"row_heading level0 row266\" >266</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col0\" class=\"data row266 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col1\" class=\"data row266 col1\" >62</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col2\" class=\"data row266 col2\" >1815999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col3\" class=\"data row266 col3\" >1922402</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col4\" class=\"data row266 col4\" >106403</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col5\" class=\"data row266 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row267\" class=\"row_heading level0 row267\" >267</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col0\" class=\"data row267 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col1\" class=\"data row267 col1\" >63</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col2\" class=\"data row267 col2\" >1898264</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col3\" class=\"data row267 col3\" >1870596</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col4\" class=\"data row267 col4\" >-27668</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col5\" class=\"data row267 col5\" >-1.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row268\" class=\"row_heading level0 row268\" >268</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col0\" class=\"data row268 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col1\" class=\"data row268 col1\" >64</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col2\" class=\"data row268 col2\" >1414222</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col3\" class=\"data row268 col3\" >1826744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col4\" class=\"data row268 col4\" >412522</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col5\" class=\"data row268 col5\" >29.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row269\" class=\"row_heading level0 row269\" >269</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col0\" class=\"data row269 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col1\" class=\"data row269 col1\" >65</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col2\" class=\"data row269 col2\" >1405839</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col3\" class=\"data row269 col3\" >1776052</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col4\" class=\"data row269 col4\" >370213</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col5\" class=\"data row269 col5\" >26.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row270\" class=\"row_heading level0 row270\" >270</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col0\" class=\"data row270 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col1\" class=\"data row270 col1\" >66</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col2\" class=\"data row270 col2\" >1381541</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col3\" class=\"data row270 col3\" >1758337</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col4\" class=\"data row270 col4\" >376796</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col5\" class=\"data row270 col5\" >27.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row271\" class=\"row_heading level0 row271\" >271</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col0\" class=\"data row271 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col1\" class=\"data row271 col1\" >67</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col2\" class=\"data row271 col2\" >1423562</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col3\" class=\"data row271 col3\" >1832243</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col4\" class=\"data row271 col4\" >408681</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col5\" class=\"data row271 col5\" >28.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row272\" class=\"row_heading level0 row272\" >272</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col0\" class=\"data row272 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col1\" class=\"data row272 col1\" >68</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col2\" class=\"data row272 col2\" >1254117</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col3\" class=\"data row272 col3\" >1361081</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col4\" class=\"data row272 col4\" >106964</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col5\" class=\"data row272 col5\" >8.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row273\" class=\"row_heading level0 row273\" >273</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col0\" class=\"data row273 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col1\" class=\"data row273 col1\" >69</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col2\" class=\"data row273 col2\" >1161048</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col3\" class=\"data row273 col3\" >1347423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col4\" class=\"data row273 col4\" >186375</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col5\" class=\"data row273 col5\" >16.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row274\" class=\"row_heading level0 row274\" >274</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col0\" class=\"data row274 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col1\" class=\"data row274 col1\" >70</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col2\" class=\"data row274 col2\" >1108504</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col3\" class=\"data row274 col3\" >1316930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col4\" class=\"data row274 col4\" >208426</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col5\" class=\"data row274 col5\" >18.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row275\" class=\"row_heading level0 row275\" >275</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col0\" class=\"data row275 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col1\" class=\"data row275 col1\" >71</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col2\" class=\"data row275 col2\" >1050349</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col3\" class=\"data row275 col3\" >1350590</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col4\" class=\"data row275 col4\" >300241</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col5\" class=\"data row275 col5\" >28.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row276\" class=\"row_heading level0 row276\" >276</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col0\" class=\"data row276 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col1\" class=\"data row276 col1\" >72</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col2\" class=\"data row276 col2\" >1021291</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col3\" class=\"data row276 col3\" >1183363</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col4\" class=\"data row276 col4\" >162072</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col5\" class=\"data row276 col5\" >15.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row277\" class=\"row_heading level0 row277\" >277</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col0\" class=\"data row277 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col1\" class=\"data row277 col1\" >73</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col2\" class=\"data row277 col2\" >955658</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col3\" class=\"data row277 col3\" >1089027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col4\" class=\"data row277 col4\" >133369</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col5\" class=\"data row277 col5\" >13.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row278\" class=\"row_heading level0 row278\" >278</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col0\" class=\"data row278 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col1\" class=\"data row278 col1\" >74</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col2\" class=\"data row278 col2\" >927165</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col3\" class=\"data row278 col3\" >1032543</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col4\" class=\"data row278 col4\" >105378</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col5\" class=\"data row278 col5\" >11.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row279\" class=\"row_heading level0 row279\" >279</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col0\" class=\"data row279 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col1\" class=\"data row279 col1\" >75</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col2\" class=\"data row279 col2\" >906215</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col3\" class=\"data row279 col3\" >970796</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col4\" class=\"data row279 col4\" >64581</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col5\" class=\"data row279 col5\" >7.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row280\" class=\"row_heading level0 row280\" >280</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col0\" class=\"data row280 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col1\" class=\"data row280 col1\" >76</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col2\" class=\"data row280 col2\" >828129</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col3\" class=\"data row280 col3\" >935833</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col4\" class=\"data row280 col4\" >107704</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col5\" class=\"data row280 col5\" >13.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row281\" class=\"row_heading level0 row281\" >281</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col0\" class=\"data row281 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col1\" class=\"data row281 col1\" >77</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col2\" class=\"data row281 col2\" >818306</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col3\" class=\"data row281 col3\" >866942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col4\" class=\"data row281 col4\" >48636</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col5\" class=\"data row281 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row282\" class=\"row_heading level0 row282\" >282</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col0\" class=\"data row282 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col1\" class=\"data row282 col1\" >78</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col2\" class=\"data row282 col2\" >799408</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col3\" class=\"data row282 col3\" >831915</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col4\" class=\"data row282 col4\" >32507</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col5\" class=\"data row282 col5\" >4.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row283\" class=\"row_heading level0 row283\" >283</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col0\" class=\"data row283 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col1\" class=\"data row283 col1\" >79</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col2\" class=\"data row283 col2\" >781027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col3\" class=\"data row283 col3\" >803078</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col4\" class=\"data row283 col4\" >22051</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col5\" class=\"data row283 col5\" >2.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row284\" class=\"row_heading level0 row284\" >284</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col0\" class=\"data row284 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col1\" class=\"data row284 col1\" >80</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col2\" class=\"data row284 col2\" >770509</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col3\" class=\"data row284 col3\" >723310</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col4\" class=\"data row284 col4\" >-47199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col5\" class=\"data row284 col5\" >-6.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row285\" class=\"row_heading level0 row285\" >285</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col0\" class=\"data row285 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col1\" class=\"data row285 col1\" >81</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col2\" class=\"data row285 col2\" >716533</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col3\" class=\"data row285 col3\" >704052</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col4\" class=\"data row285 col4\" >-12481</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col5\" class=\"data row285 col5\" >-1.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row286\" class=\"row_heading level0 row286\" >286</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col0\" class=\"data row286 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col1\" class=\"data row286 col1\" >82</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col2\" class=\"data row286 col2\" >695544</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col3\" class=\"data row286 col3\" >675643</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col4\" class=\"data row286 col4\" >-19901</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col5\" class=\"data row286 col5\" >-2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row287\" class=\"row_heading level0 row287\" >287</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col0\" class=\"data row287 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col1\" class=\"data row287 col1\" >83</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col2\" class=\"data row287 col2\" >658441</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col3\" class=\"data row287 col3\" >647071</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col4\" class=\"data row287 col4\" >-11370</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col5\" class=\"data row287 col5\" >-1.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row288\" class=\"row_heading level0 row288\" >288</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col0\" class=\"data row288 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col1\" class=\"data row288 col1\" >84</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col2\" class=\"data row288 col2\" >611338</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col3\" class=\"data row288 col3\" >623984</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col4\" class=\"data row288 col4\" >12646</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col5\" class=\"data row288 col5\" >2.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row289\" class=\"row_heading level0 row289\" >289</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col0\" class=\"data row289 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col1\" class=\"data row289 col1\" >85</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col2\" class=\"data row289 col2\" >577352</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col3\" class=\"data row289 col3\" >564605</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col4\" class=\"data row289 col4\" >-12747</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col5\" class=\"data row289 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row290\" class=\"row_heading level0 row290\" >290</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col0\" class=\"data row290 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col1\" class=\"data row290 col1\" >86</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col2\" class=\"data row290 col2\" >526153</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col3\" class=\"data row290 col3\" >531680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col4\" class=\"data row290 col4\" >5527</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col5\" class=\"data row290 col5\" >1.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row291\" class=\"row_heading level0 row291\" >291</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col0\" class=\"data row291 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col1\" class=\"data row291 col1\" >87</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col2\" class=\"data row291 col2\" >467575</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col3\" class=\"data row291 col3\" >486253</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col4\" class=\"data row291 col4\" >18678</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col5\" class=\"data row291 col5\" >3.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row292\" class=\"row_heading level0 row292\" >292</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col0\" class=\"data row292 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col1\" class=\"data row292 col1\" >88</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col2\" class=\"data row292 col2\" >420437</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col3\" class=\"data row292 col3\" >433947</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col4\" class=\"data row292 col4\" >13510</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col5\" class=\"data row292 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row293\" class=\"row_heading level0 row293\" >293</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col0\" class=\"data row293 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col1\" class=\"data row293 col1\" >89</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col2\" class=\"data row293 col2\" >365732</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col3\" class=\"data row293 col3\" >392978</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col4\" class=\"data row293 col4\" >27246</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col5\" class=\"data row293 col5\" >7.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row294\" class=\"row_heading level0 row294\" >294</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col0\" class=\"data row294 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col1\" class=\"data row294 col1\" >90</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col2\" class=\"data row294 col2\" >306925</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col3\" class=\"data row294 col3\" >341430</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col4\" class=\"data row294 col4\" >34505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col5\" class=\"data row294 col5\" >11.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row295\" class=\"row_heading level0 row295\" >295</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col0\" class=\"data row295 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col1\" class=\"data row295 col1\" >91</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col2\" class=\"data row295 col2\" >240151</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col3\" class=\"data row295 col3\" >287889</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col4\" class=\"data row295 col4\" >47738</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col5\" class=\"data row295 col5\" >19.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row296\" class=\"row_heading level0 row296\" >296</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col0\" class=\"data row296 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col1\" class=\"data row296 col1\" >92</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col2\" class=\"data row296 col2\" >205379</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col3\" class=\"data row296 col3\" >243648</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col4\" class=\"data row296 col4\" >38269</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col5\" class=\"data row296 col5\" >18.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row297\" class=\"row_heading level0 row297\" >297</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col0\" class=\"data row297 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col1\" class=\"data row297 col1\" >93</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col2\" class=\"data row297 col2\" >158882</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col3\" class=\"data row297 col3\" >199426</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col4\" class=\"data row297 col4\" >40544</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col5\" class=\"data row297 col5\" >25.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row298\" class=\"row_heading level0 row298\" >298</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col0\" class=\"data row298 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col1\" class=\"data row298 col1\" >94</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col2\" class=\"data row298 col2\" >126948</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col3\" class=\"data row298 col3\" >155637</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col4\" class=\"data row298 col4\" >28689</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col5\" class=\"data row298 col5\" >22.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row299\" class=\"row_heading level0 row299\" >299</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col0\" class=\"data row299 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col1\" class=\"data row299 col1\" >95</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col2\" class=\"data row299 col2\" >99341</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col3\" class=\"data row299 col3\" >113732</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col4\" class=\"data row299 col4\" >14391</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col5\" class=\"data row299 col5\" >14.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row300\" class=\"row_heading level0 row300\" >300</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col0\" class=\"data row300 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col1\" class=\"data row300 col1\" >96</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col2\" class=\"data row300 col2\" >75139</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col3\" class=\"data row300 col3\" >89432</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col4\" class=\"data row300 col4\" >14293</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col5\" class=\"data row300 col5\" >19.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row301\" class=\"row_heading level0 row301\" >301</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col0\" class=\"data row301 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col1\" class=\"data row301 col1\" >97</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col2\" class=\"data row301 col2\" >54118</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col3\" class=\"data row301 col3\" >62779</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col4\" class=\"data row301 col4\" >8661</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col5\" class=\"data row301 col5\" >16.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row302\" class=\"row_heading level0 row302\" >302</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col0\" class=\"data row302 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col1\" class=\"data row302 col1\" >98</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col2\" class=\"data row302 col2\" >37532</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col3\" class=\"data row302 col3\" >46208</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col4\" class=\"data row302 col4\" >8676</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col5\" class=\"data row302 col5\" >23.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row303\" class=\"row_heading level0 row303\" >303</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col0\" class=\"data row303 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col1\" class=\"data row303 col1\" >99</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col2\" class=\"data row303 col2\" >26074</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col3\" class=\"data row303 col3\" >32517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col4\" class=\"data row303 col4\" >6443</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col5\" class=\"data row303 col5\" >24.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row304\" class=\"row_heading level0 row304\" >304</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col0\" class=\"data row304 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col1\" class=\"data row304 col1\" >100</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col2\" class=\"data row304 col2\" >45058</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col3\" class=\"data row304 col3\" >58008</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col4\" class=\"data row304 col4\" >12950</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col5\" class=\"data row304 col5\" >28.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row305\" class=\"row_heading level0 row305\" >305</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col0\" class=\"data row305 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col1\" class=\"data row305 col1\" >999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col2\" class=\"data row305 col2\" >157258820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col3\" class=\"data row305 col3\" >161952064</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col4\" class=\"data row305 col4\" >4693244</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col5\" class=\"data row305 col5\" >2.98%</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd9c2be5e50>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "change = us_pop['2014'] - us_pop['2010']\n",
+    "\n",
+    "\n",
+    "census = us_pop\n",
+    "\n",
+    "census['Change'] = change\n",
+    "\n",
+    "census['Percent Change'] = change/us_pop['2010']\n",
+    "\n",
+    "census.style.format({'Percent Change': \"{:,.2%}\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Sorting the data.** Let us sort the table in decreasing order of the absolute change in population."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_3daade6a_5280_11eb_8c0f_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >SEX</th>        <th class=\"col_heading level0 col1\" >AGE</th>        <th class=\"col_heading level0 col2\" >2010</th>        <th class=\"col_heading level0 col3\" >2014</th>        <th class=\"col_heading level0 col4\" >Change</th>        <th class=\"col_heading level0 col5\" >Percent Change</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row0\" class=\"row_heading level0 row0\" >101</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col0\" class=\"data row0 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col1\" class=\"data row0 col1\" >999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col2\" class=\"data row0 col2\" >309346863</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col3\" class=\"data row0 col3\" >318907401</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col4\" class=\"data row0 col4\" >9560538</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col5\" class=\"data row0 col5\" >3.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row1\" class=\"row_heading level0 row1\" >203</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col0\" class=\"data row1 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col1\" class=\"data row1 col1\" >999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col2\" class=\"data row1 col2\" >152088043</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col3\" class=\"data row1 col3\" >156955337</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col4\" class=\"data row1 col4\" >4867294</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col5\" class=\"data row1 col5\" >3.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row2\" class=\"row_heading level0 row2\" >305</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col0\" class=\"data row2 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col1\" class=\"data row2 col1\" >999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col2\" class=\"data row2 col2\" >157258820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col3\" class=\"data row2 col3\" >161952064</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col4\" class=\"data row2 col4\" >4693244</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col5\" class=\"data row2 col5\" >2.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row3\" class=\"row_heading level0 row3\" >67</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col0\" class=\"data row3 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col1\" class=\"data row3 col1\" >67</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col2\" class=\"data row3 col2\" >2693707</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col3\" class=\"data row3 col3\" >3485241</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col4\" class=\"data row3 col4\" >791534</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col5\" class=\"data row3 col5\" >29.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row4\" class=\"row_heading level0 row4\" >64</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col0\" class=\"data row4 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col1\" class=\"data row4 col1\" >64</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col2\" class=\"data row4 col2\" >2706055</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col3\" class=\"data row4 col3\" >3487559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col4\" class=\"data row4 col4\" >781504</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col5\" class=\"data row4 col5\" >28.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row5\" class=\"row_heading level0 row5\" >66</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col0\" class=\"data row5 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col1\" class=\"data row5 col1\" >66</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col2\" class=\"data row5 col2\" >2621335</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col3\" class=\"data row5 col3\" >3347060</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col4\" class=\"data row5 col4\" >725725</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col5\" class=\"data row5 col5\" >27.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row6\" class=\"row_heading level0 row6\" >65</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col0\" class=\"data row6 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col1\" class=\"data row6 col1\" >65</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col2\" class=\"data row6 col2\" >2678525</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col3\" class=\"data row6 col3\" >3382824</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col4\" class=\"data row6 col4\" >704299</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col5\" class=\"data row6 col5\" >26.29%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row7\" class=\"row_heading level0 row7\" >71</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col0\" class=\"data row7 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col1\" class=\"data row7 col1\" >71</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col2\" class=\"data row7 col2\" >1953607</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col3\" class=\"data row7 col3\" >2519705</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col4\" class=\"data row7 col4\" >566098</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col5\" class=\"data row7 col5\" >28.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row8\" class=\"row_heading level0 row8\" >34</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col0\" class=\"data row8 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col1\" class=\"data row8 col1\" >34</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col2\" class=\"data row8 col2\" >3822189</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col3\" class=\"data row8 col3\" >4364748</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col4\" class=\"data row8 col4\" >542559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col5\" class=\"data row8 col5\" >14.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row9\" class=\"row_heading level0 row9\" >23</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col0\" class=\"data row9 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col1\" class=\"data row9 col1\" >23</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col2\" class=\"data row9 col2\" >4217228</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col3\" class=\"data row9 col3\" >4702156</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col4\" class=\"data row9 col4\" >484928</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col5\" class=\"data row9 col5\" >11.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row10\" class=\"row_heading level0 row10\" >59</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col0\" class=\"data row10 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col1\" class=\"data row10 col1\" >59</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col2\" class=\"data row10 col2\" >3694254</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col3\" class=\"data row10 col3\" >4155521</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col4\" class=\"data row10 col4\" >461267</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col5\" class=\"data row10 col5\" >12.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row11\" class=\"row_heading level0 row11\" >24</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col0\" class=\"data row11 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col1\" class=\"data row11 col1\" >24</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col2\" class=\"data row11 col2\" >4243602</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col3\" class=\"data row11 col3\" >4695411</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col4\" class=\"data row11 col4\" >451809</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col5\" class=\"data row11 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row12\" class=\"row_heading level0 row12\" >268</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col0\" class=\"data row12 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col1\" class=\"data row12 col1\" >64</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col2\" class=\"data row12 col2\" >1414222</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col3\" class=\"data row12 col3\" >1826744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col4\" class=\"data row12 col4\" >412522</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col5\" class=\"data row12 col5\" >29.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row13\" class=\"row_heading level0 row13\" >271</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col0\" class=\"data row13 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col1\" class=\"data row13 col1\" >67</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col2\" class=\"data row13 col2\" >1423562</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col3\" class=\"data row13 col3\" >1832243</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col4\" class=\"data row13 col4\" >408681</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col5\" class=\"data row13 col5\" >28.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row14\" class=\"row_heading level0 row14\" >70</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col0\" class=\"data row14 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col1\" class=\"data row14 col1\" >70</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col2\" class=\"data row14 col2\" >2062577</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col3\" class=\"data row14 col3\" >2465438</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col4\" class=\"data row14 col4\" >402861</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col5\" class=\"data row14 col5\" >19.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row15\" class=\"row_heading level0 row15\" >57</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col0\" class=\"data row15 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col1\" class=\"data row15 col1\" >57</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col2\" class=\"data row15 col2\" >3946518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col3\" class=\"data row15 col3\" >4347023</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col4\" class=\"data row15 col4\" >400505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col5\" class=\"data row15 col5\" >10.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row16\" class=\"row_heading level0 row16\" >58</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col0\" class=\"data row16 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col1\" class=\"data row16 col1\" >58</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col2\" class=\"data row16 col2\" >3802447</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col3\" class=\"data row16 col3\" >4191360</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col4\" class=\"data row16 col4\" >388913</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col5\" class=\"data row16 col5\" >10.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row17\" class=\"row_heading level0 row17\" >169</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col0\" class=\"data row17 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col1\" class=\"data row17 col1\" >67</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col2\" class=\"data row17 col2\" >1270145</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col3\" class=\"data row17 col3\" >1652998</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col4\" class=\"data row17 col4\" >382853</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col5\" class=\"data row17 col5\" >30.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row18\" class=\"row_heading level0 row18\" >270</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col0\" class=\"data row18 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col1\" class=\"data row18 col1\" >66</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col2\" class=\"data row18 col2\" >1381541</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col3\" class=\"data row18 col3\" >1758337</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col4\" class=\"data row18 col4\" >376796</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col5\" class=\"data row18 col5\" >27.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row19\" class=\"row_heading level0 row19\" >269</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col0\" class=\"data row19 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col1\" class=\"data row19 col1\" >65</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col2\" class=\"data row19 col2\" >1405839</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col3\" class=\"data row19 col3\" >1776052</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col4\" class=\"data row19 col4\" >370213</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col5\" class=\"data row19 col5\" >26.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row20\" class=\"row_heading level0 row20\" >166</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col0\" class=\"data row20 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col1\" class=\"data row20 col1\" >64</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col2\" class=\"data row20 col2\" >1291833</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col3\" class=\"data row20 col3\" >1660815</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col4\" class=\"data row20 col4\" >368982</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col5\" class=\"data row20 col5\" >28.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row21\" class=\"row_heading level0 row21\" >60</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col0\" class=\"data row21 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col1\" class=\"data row21 col1\" >60</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col2\" class=\"data row21 col2\" >3616721</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col3\" class=\"data row21 col3\" >3985598</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col4\" class=\"data row21 col4\" >368877</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col5\" class=\"data row21 col5\" >10.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row22\" class=\"row_heading level0 row22\" >69</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col0\" class=\"data row22 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col1\" class=\"data row22 col1\" >69</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col2\" class=\"data row22 col2\" >2167830</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col3\" class=\"data row22 col3\" >2534295</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col4\" class=\"data row22 col4\" >366465</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col5\" class=\"data row22 col5\" >16.90%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row23\" class=\"row_heading level0 row23\" >32</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col0\" class=\"data row23 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col1\" class=\"data row23 col1\" >32</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col2\" class=\"data row23 col2\" >3967602</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col3\" class=\"data row23 col3\" >4323951</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col4\" class=\"data row23 col4\" >356349</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col5\" class=\"data row23 col5\" >8.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row24\" class=\"row_heading level0 row24\" >168</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col0\" class=\"data row24 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col1\" class=\"data row24 col1\" >66</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col2\" class=\"data row24 col2\" >1239794</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col3\" class=\"data row24 col3\" >1588723</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col4\" class=\"data row24 col4\" >348929</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col5\" class=\"data row24 col5\" >28.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row25\" class=\"row_heading level0 row25\" >33</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col0\" class=\"data row25 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col1\" class=\"data row25 col1\" >33</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col2\" class=\"data row25 col2\" >3933581</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col3\" class=\"data row25 col3\" >4278664</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col4\" class=\"data row25 col4\" >345083</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col5\" class=\"data row25 col5\" >8.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row26\" class=\"row_heading level0 row26\" >167</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col0\" class=\"data row26 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col1\" class=\"data row26 col1\" >65</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col2\" class=\"data row26 col2\" >1272686</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col3\" class=\"data row26 col3\" >1606772</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col4\" class=\"data row26 col4\" >334086</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col5\" class=\"data row26 col5\" >26.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row27\" class=\"row_heading level0 row27\" >22</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col0\" class=\"data row27 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col1\" class=\"data row27 col1\" >22</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col2\" class=\"data row27 col2\" >4287005</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col3\" class=\"data row27 col3\" >4615729</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col4\" class=\"data row27 col4\" >328724</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col5\" class=\"data row27 col5\" >7.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row28\" class=\"row_heading level0 row28\" >61</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col0\" class=\"data row28 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col1\" class=\"data row28 col1\" >61</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col2\" class=\"data row28 col2\" >3520109</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col3\" class=\"data row28 col3\" >3834367</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col4\" class=\"data row28 col4\" >314258</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col5\" class=\"data row28 col5\" >8.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row29\" class=\"row_heading level0 row29\" >72</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col0\" class=\"data row29 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col1\" class=\"data row29 col1\" >72</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col2\" class=\"data row29 col2\" >1883820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col3\" class=\"data row29 col3\" >2193945</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col4\" class=\"data row29 col4\" >310125</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col5\" class=\"data row29 col5\" >16.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row30\" class=\"row_heading level0 row30\" >56</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col0\" class=\"data row30 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col1\" class=\"data row30 col1\" >56</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col2\" class=\"data row30 col2\" >4093136</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col3\" class=\"data row30 col3\" >4395949</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col4\" class=\"data row30 col4\" >302813</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col5\" class=\"data row30 col5\" >7.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row31\" class=\"row_heading level0 row31\" >275</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col0\" class=\"data row31 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col1\" class=\"data row31 col1\" >71</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col2\" class=\"data row31 col2\" >1050349</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col3\" class=\"data row31 col3\" >1350590</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col4\" class=\"data row31 col4\" >300241</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col5\" class=\"data row31 col5\" >28.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row32\" class=\"row_heading level0 row32\" >54</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col0\" class=\"data row32 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col1\" class=\"data row32 col1\" >54</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col2\" class=\"data row32 col2\" >4288447</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col3\" class=\"data row32 col3\" >4574760</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col4\" class=\"data row32 col4\" >286313</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col5\" class=\"data row32 col5\" >6.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row33\" class=\"row_heading level0 row33\" >136</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col0\" class=\"data row33 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col1\" class=\"data row33 col1\" >34</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col2\" class=\"data row33 col2\" >1908731</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col3\" class=\"data row33 col3\" >2192877</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col4\" class=\"data row33 col4\" >284146</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col5\" class=\"data row33 col5\" >14.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row34\" class=\"row_heading level0 row34\" >31</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col0\" class=\"data row34 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col1\" class=\"data row34 col1\" >31</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col2\" class=\"data row34 col2\" >4042516</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col3\" class=\"data row34 col3\" >4323217</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col4\" class=\"data row34 col4\" >280701</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col5\" class=\"data row34 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row35\" class=\"row_heading level0 row35\" >173</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col0\" class=\"data row35 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col1\" class=\"data row35 col1\" >71</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col2\" class=\"data row35 col2\" >903258</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col3\" class=\"data row35 col3\" >1169115</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col4\" class=\"data row35 col4\" >265857</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col5\" class=\"data row35 col5\" >29.43%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row36\" class=\"row_heading level0 row36\" >238</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col0\" class=\"data row36 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col1\" class=\"data row36 col1\" >34</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col2\" class=\"data row36 col2\" >1913458</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col3\" class=\"data row36 col3\" >2171871</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col4\" class=\"data row36 col4\" >258413</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col5\" class=\"data row36 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row37\" class=\"row_heading level0 row37\" >73</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col0\" class=\"data row37 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col1\" class=\"data row37 col1\" >73</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col2\" class=\"data row37 col2\" >1750304</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col3\" class=\"data row37 col3\" >2001700</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col4\" class=\"data row37 col4\" >251396</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col5\" class=\"data row37 col5\" >14.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row38\" class=\"row_heading level0 row38\" >125</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col0\" class=\"data row38 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col1\" class=\"data row38 col1\" >23</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col2\" class=\"data row38 col2\" >2151068</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col3\" class=\"data row38 col3\" >2402294</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col4\" class=\"data row38 col4\" >251226</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col5\" class=\"data row38 col5\" >11.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row39\" class=\"row_heading level0 row39\" >26</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col0\" class=\"data row39 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col1\" class=\"data row39 col1\" >26</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col2\" class=\"data row39 col2\" >4160806</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col3\" class=\"data row39 col3\" >4408043</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col4\" class=\"data row39 col4\" >247237</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col5\" class=\"data row39 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row40\" class=\"row_heading level0 row40\" >43</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col0\" class=\"data row40 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col1\" class=\"data row40 col1\" >43</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col2\" class=\"data row40 col2\" >4093844</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col3\" class=\"data row40 col3\" >4333850</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col4\" class=\"data row40 col4\" >240006</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col5\" class=\"data row40 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row41\" class=\"row_heading level0 row41\" >263</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col0\" class=\"data row41 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col1\" class=\"data row41 col1\" >59</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col2\" class=\"data row41 col2\" >1914774</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col3\" class=\"data row41 col3\" >2148934</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col4\" class=\"data row41 col4\" >234160</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col5\" class=\"data row41 col5\" >12.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row42\" class=\"row_heading level0 row42\" >227</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col0\" class=\"data row42 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col1\" class=\"data row42 col1\" >23</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col2\" class=\"data row42 col2\" >2066160</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col3\" class=\"data row42 col3\" >2299862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col4\" class=\"data row42 col4\" >233702</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col5\" class=\"data row42 col5\" >11.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row43\" class=\"row_heading level0 row43\" >126</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col0\" class=\"data row43 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col1\" class=\"data row43 col1\" >24</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col2\" class=\"data row43 col2\" >2161347</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col3\" class=\"data row43 col3\" >2393037</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col4\" class=\"data row43 col4\" >231690</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col5\" class=\"data row43 col5\" >10.72%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row44\" class=\"row_heading level0 row44\" >161</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col0\" class=\"data row44 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col1\" class=\"data row44 col1\" >59</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col2\" class=\"data row44 col2\" >1779480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col3\" class=\"data row44 col3\" >2006587</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col4\" class=\"data row44 col4\" >227107</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col5\" class=\"data row44 col5\" >12.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row45\" class=\"row_heading level0 row45\" >25</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col0\" class=\"data row45 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col1\" class=\"data row45 col1\" >25</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col2\" class=\"data row45 col2\" >4289428</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col3\" class=\"data row45 col3\" >4511370</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col4\" class=\"data row45 col4\" >221942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col5\" class=\"data row45 col5\" >5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row46\" class=\"row_heading level0 row46\" >228</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col0\" class=\"data row46 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col1\" class=\"data row46 col1\" >24</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col2\" class=\"data row46 col2\" >2082255</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col3\" class=\"data row46 col3\" >2302374</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col4\" class=\"data row46 col4\" >220119</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col5\" class=\"data row46 col5\" >10.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row47\" class=\"row_heading level0 row47\" >68</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col0\" class=\"data row47 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col1\" class=\"data row47 col1\" >68</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col2\" class=\"data row47 col2\" >2359816</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col3\" class=\"data row47 col3\" >2572359</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col4\" class=\"data row47 col4\" >212543</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col5\" class=\"data row47 col5\" >9.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row48\" class=\"row_heading level0 row48\" >76</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col0\" class=\"data row48 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col1\" class=\"data row48 col1\" >76</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col2\" class=\"data row48 col2\" >1481680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col3\" class=\"data row48 col3\" >1693674</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col4\" class=\"data row48 col4\" >211994</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col5\" class=\"data row48 col5\" >14.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row49\" class=\"row_heading level0 row49\" >44</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col0\" class=\"data row49 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col1\" class=\"data row49 col1\" >44</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col2\" class=\"data row49 col2\" >4178508</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col3\" class=\"data row49 col3\" >4390283</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col4\" class=\"data row49 col4\" >211775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col5\" class=\"data row49 col5\" >5.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row50\" class=\"row_heading level0 row50\" >274</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col0\" class=\"data row50 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col1\" class=\"data row50 col1\" >70</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col2\" class=\"data row50 col2\" >1108504</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col3\" class=\"data row50 col3\" >1316930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col4\" class=\"data row50 col4\" >208426</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col5\" class=\"data row50 col5\" >18.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row51\" class=\"row_heading level0 row51\" >74</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col0\" class=\"data row51 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col1\" class=\"data row51 col1\" >74</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col2\" class=\"data row51 col2\" >1685995</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col3\" class=\"data row51 col3\" >1889513</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col4\" class=\"data row51 col4\" >203518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col5\" class=\"data row51 col5\" >12.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row52\" class=\"row_heading level0 row52\" >261</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col0\" class=\"data row52 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col1\" class=\"data row52 col1\" >57</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col2\" class=\"data row52 col2\" >2036521</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col3\" class=\"data row52 col3\" >2237219</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col4\" class=\"data row52 col4\" >200698</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col5\" class=\"data row52 col5\" >9.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row53\" class=\"row_heading level0 row53\" >262</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col0\" class=\"data row53 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col1\" class=\"data row53 col1\" >58</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col2\" class=\"data row53 col2\" >1963767</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col3\" class=\"data row53 col3\" >2163908</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col4\" class=\"data row53 col4\" >200141</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col5\" class=\"data row53 col5\" >10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row54\" class=\"row_heading level0 row54\" >159</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col0\" class=\"data row54 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col1\" class=\"data row54 col1\" >57</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col2\" class=\"data row54 col2\" >1909997</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col3\" class=\"data row54 col3\" >2109804</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col4\" class=\"data row54 col4\" >199807</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col5\" class=\"data row54 col5\" >10.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row55\" class=\"row_heading level0 row55\" >264</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col0\" class=\"data row55 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col1\" class=\"data row55 col1\" >60</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col2\" class=\"data row55 col2\" >1874501</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col3\" class=\"data row55 col3\" >2071869</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col4\" class=\"data row55 col4\" >197368</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col5\" class=\"data row55 col5\" >10.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row56\" class=\"row_heading level0 row56\" >172</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col0\" class=\"data row56 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col1\" class=\"data row56 col1\" >70</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col2\" class=\"data row56 col2\" >954073</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col3\" class=\"data row56 col3\" >1148508</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col4\" class=\"data row56 col4\" >194435</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col5\" class=\"data row56 col5\" >20.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row57\" class=\"row_heading level0 row57\" >62</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col0\" class=\"data row57 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col1\" class=\"data row57 col1\" >62</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col2\" class=\"data row57 col2\" >3495059</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col3\" class=\"data row57 col3\" >3685282</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col4\" class=\"data row57 col4\" >190223</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col5\" class=\"data row57 col5\" >5.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row58\" class=\"row_heading level0 row58\" >160</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col0\" class=\"data row58 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col1\" class=\"data row58 col1\" >58</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col2\" class=\"data row58 col2\" >1838680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col3\" class=\"data row58 col3\" >2027452</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col4\" class=\"data row58 col4\" >188772</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col5\" class=\"data row58 col5\" >10.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row59\" class=\"row_heading level0 row59\" >36</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col0\" class=\"data row59 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col1\" class=\"data row59 col1\" >36</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col2\" class=\"data row59 col2\" >3830199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col3\" class=\"data row59 col3\" >4016711</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col4\" class=\"data row59 col4\" >186512</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col5\" class=\"data row59 col5\" >4.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row60\" class=\"row_heading level0 row60\" >273</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col0\" class=\"data row60 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col1\" class=\"data row60 col1\" >69</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col2\" class=\"data row60 col2\" >1161048</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col3\" class=\"data row60 col3\" >1347423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col4\" class=\"data row60 col4\" >186375</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col5\" class=\"data row60 col5\" >16.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row61\" class=\"row_heading level0 row61\" >124</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col0\" class=\"data row61 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col1\" class=\"data row61 col1\" >22</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col2\" class=\"data row61 col2\" >2188199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col3\" class=\"data row61 col3\" >2370459</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col4\" class=\"data row61 col4\" >182260</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col5\" class=\"data row61 col5\" >8.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row62\" class=\"row_heading level0 row62\" >29</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col0\" class=\"data row62 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col1\" class=\"data row62 col1\" >29</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col2\" class=\"data row62 col2\" >4210286</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col3\" class=\"data row62 col3\" >4391788</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col4\" class=\"data row62 col4\" >181502</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col5\" class=\"data row62 col5\" >4.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row63\" class=\"row_heading level0 row63\" >134</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col0\" class=\"data row63 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col1\" class=\"data row63 col1\" >32</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col2\" class=\"data row63 col2\" >1986147</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col3\" class=\"data row63 col3\" >2167557</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col4\" class=\"data row63 col4\" >181410</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col5\" class=\"data row63 col5\" >9.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row64\" class=\"row_heading level0 row64\" >171</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col0\" class=\"data row64 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col1\" class=\"data row64 col1\" >69</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col2\" class=\"data row64 col2\" >1006782</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col3\" class=\"data row64 col3\" >1186872</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col4\" class=\"data row64 col4\" >180090</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col5\" class=\"data row64 col5\" >17.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row65\" class=\"row_heading level0 row65\" >135</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col0\" class=\"data row65 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col1\" class=\"data row65 col1\" >33</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col2\" class=\"data row65 col2\" >1963645</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col3\" class=\"data row65 col3\" >2141552</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col4\" class=\"data row65 col4\" >177907</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col5\" class=\"data row65 col5\" >9.06%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row66\" class=\"row_heading level0 row66\" >236</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col0\" class=\"data row66 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col1\" class=\"data row66 col1\" >32</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col2\" class=\"data row66 col2\" >1981455</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col3\" class=\"data row66 col3\" >2156394</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col4\" class=\"data row66 col4\" >174939</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col5\" class=\"data row66 col5\" >8.83%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row67\" class=\"row_heading level0 row67\" >162</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col0\" class=\"data row67 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col1\" class=\"data row67 col1\" >60</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col2\" class=\"data row67 col2\" >1742220</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col3\" class=\"data row67 col3\" >1913729</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col4\" class=\"data row67 col4\" >171509</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col5\" class=\"data row67 col5\" >9.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row68\" class=\"row_heading level0 row68\" >265</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col0\" class=\"data row68 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col1\" class=\"data row68 col1\" >61</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col2\" class=\"data row68 col2\" >1828708</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col3\" class=\"data row68 col3\" >1997711</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col4\" class=\"data row68 col4\" >169003</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col5\" class=\"data row68 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row69\" class=\"row_heading level0 row69\" >237</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col0\" class=\"data row69 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col1\" class=\"data row69 col1\" >33</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col2\" class=\"data row69 col2\" >1969936</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col3\" class=\"data row69 col3\" >2137112</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col4\" class=\"data row69 col4\" >167176</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col5\" class=\"data row69 col5\" >8.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row70\" class=\"row_heading level0 row70\" >55</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col0\" class=\"data row70 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col1\" class=\"data row70 col1\" >55</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col2\" class=\"data row70 col2\" >4258970</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col3\" class=\"data row70 col3\" >4421856</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col4\" class=\"data row70 col4\" >162886</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col5\" class=\"data row70 col5\" >3.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row71\" class=\"row_heading level0 row71\" >276</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col0\" class=\"data row71 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col1\" class=\"data row71 col1\" >72</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col2\" class=\"data row71 col2\" >1021291</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col3\" class=\"data row71 col3\" >1183363</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col4\" class=\"data row71 col4\" >162072</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col5\" class=\"data row71 col5\" >15.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row72\" class=\"row_heading level0 row72\" >158</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col0\" class=\"data row72 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col1\" class=\"data row72 col1\" >56</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col2\" class=\"data row72 col2\" >1984452</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col3\" class=\"data row72 col3\" >2140940</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col4\" class=\"data row72 col4\" >156488</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col5\" class=\"data row72 col5\" >7.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row73\" class=\"row_heading level0 row73\" >156</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col0\" class=\"data row73 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col1\" class=\"data row73 col1\" >54</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col2\" class=\"data row73 col2\" >2091640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col3\" class=\"data row73 col3\" >2242757</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col4\" class=\"data row73 col4\" >151117</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col5\" class=\"data row73 col5\" >7.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row74\" class=\"row_heading level0 row74\" >174</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col0\" class=\"data row74 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col1\" class=\"data row74 col1\" >72</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col2\" class=\"data row74 col2\" >862529</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col3\" class=\"data row74 col3\" >1010582</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col4\" class=\"data row74 col4\" >148053</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col5\" class=\"data row74 col5\" >17.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row75\" class=\"row_heading level0 row75\" >35</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col0\" class=\"data row75 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col1\" class=\"data row75 col1\" >35</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col2\" class=\"data row75 col2\" >3948335</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col3\" class=\"data row75 col3\" >4095782</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col4\" class=\"data row75 col4\" >147447</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col5\" class=\"data row75 col5\" >3.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row76\" class=\"row_heading level0 row76\" >226</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col0\" class=\"data row76 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col1\" class=\"data row76 col1\" >22</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col2\" class=\"data row76 col2\" >2098806</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col3\" class=\"data row76 col3\" >2245270</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col4\" class=\"data row76 col4\" >146464</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col5\" class=\"data row76 col5\" >6.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row77\" class=\"row_heading level0 row77\" >260</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col0\" class=\"data row77 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col1\" class=\"data row77 col1\" >56</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col2\" class=\"data row77 col2\" >2108684</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col3\" class=\"data row77 col3\" >2255009</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col4\" class=\"data row77 col4\" >146325</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col5\" class=\"data row77 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row78\" class=\"row_heading level0 row78\" >133</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col0\" class=\"data row78 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col1\" class=\"data row78 col1\" >31</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col2\" class=\"data row78 col2\" >2026439</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col3\" class=\"data row78 col3\" >2171839</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col4\" class=\"data row78 col4\" >145400</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col5\" class=\"data row78 col5\" >7.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row79\" class=\"row_heading level0 row79\" >163</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col0\" class=\"data row79 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col1\" class=\"data row79 col1\" >61</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col2\" class=\"data row79 col2\" >1691401</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col3\" class=\"data row79 col3\" >1836656</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col4\" class=\"data row79 col4\" >145255</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col5\" class=\"data row79 col5\" >8.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row80\" class=\"row_heading level0 row80\" >75</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col0\" class=\"data row80 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col1\" class=\"data row80 col1\" >75</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col2\" class=\"data row80 col2\" >1631878</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col3\" class=\"data row80 col3\" >1773756</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col4\" class=\"data row80 col4\" >141878</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col5\" class=\"data row80 col5\" >8.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row81\" class=\"row_heading level0 row81\" >128</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col0\" class=\"data row81 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col1\" class=\"data row81 col1\" >26</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col2\" class=\"data row81 col2\" >2102331</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col3\" class=\"data row81 col3\" >2240881</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col4\" class=\"data row81 col4\" >138550</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col5\" class=\"data row81 col5\" >6.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row82\" class=\"row_heading level0 row82\" >235</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col0\" class=\"data row82 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col1\" class=\"data row82 col1\" >31</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col2\" class=\"data row82 col2\" >2016077</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col3\" class=\"data row82 col3\" >2151378</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col4\" class=\"data row82 col4\" >135301</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col5\" class=\"data row82 col5\" >6.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row83\" class=\"row_heading level0 row83\" >258</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col0\" class=\"data row83 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col1\" class=\"data row83 col1\" >54</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col2\" class=\"data row83 col2\" >2196807</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col3\" class=\"data row83 col3\" >2332003</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col4\" class=\"data row83 col4\" >135196</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col5\" class=\"data row83 col5\" >6.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row84\" class=\"row_heading level0 row84\" >277</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col0\" class=\"data row84 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col1\" class=\"data row84 col1\" >73</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col2\" class=\"data row84 col2\" >955658</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col3\" class=\"data row84 col3\" >1089027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col4\" class=\"data row84 col4\" >133369</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col5\" class=\"data row84 col5\" >13.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row85\" class=\"row_heading level0 row85\" >247</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col0\" class=\"data row85 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col1\" class=\"data row85 col1\" >43</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col2\" class=\"data row85 col2\" >2062862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col3\" class=\"data row85 col3\" >2185890</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col4\" class=\"data row85 col4\" >123028</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col5\" class=\"data row85 col5\" >5.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row86\" class=\"row_heading level0 row86\" >127</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col0\" class=\"data row86 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col1\" class=\"data row86 col1\" >25</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col2\" class=\"data row86 col2\" >2177131</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col3\" class=\"data row86 col3\" >2296875</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col4\" class=\"data row86 col4\" >119744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col5\" class=\"data row86 col5\" >5.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row87\" class=\"row_heading level0 row87\" >175</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col0\" class=\"data row87 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col1\" class=\"data row87 col1\" >73</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col2\" class=\"data row87 col2\" >794646</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col3\" class=\"data row87 col3\" >912673</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col4\" class=\"data row87 col4\" >118027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col5\" class=\"data row87 col5\" >14.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row88\" class=\"row_heading level0 row88\" >145</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col0\" class=\"data row88 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col1\" class=\"data row88 col1\" >43</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col2\" class=\"data row88 col2\" >2030982</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col3\" class=\"data row88 col3\" >2147960</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col4\" class=\"data row88 col4\" >116978</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col5\" class=\"data row88 col5\" >5.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row89\" class=\"row_heading level0 row89\" >7</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col0\" class=\"data row89 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col1\" class=\"data row89 col1\" >7</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col2\" class=\"data row89 col2\" >4043046</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col3\" class=\"data row89 col3\" >4155326</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col4\" class=\"data row89 col4\" >112280</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col5\" class=\"data row89 col5\" >2.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row90\" class=\"row_heading level0 row90\" >146</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col0\" class=\"data row90 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col1\" class=\"data row90 col1\" >44</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col2\" class=\"data row90 col2\" >2074572</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col3\" class=\"data row90 col3\" >2184448</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col4\" class=\"data row90 col4\" >109876</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col5\" class=\"data row90 col5\" >5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row91\" class=\"row_heading level0 row91\" >230</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col0\" class=\"data row91 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col1\" class=\"data row91 col1\" >26</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col2\" class=\"data row91 col2\" >2058475</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col3\" class=\"data row91 col3\" >2167162</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col4\" class=\"data row91 col4\" >108687</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col5\" class=\"data row91 col5\" >5.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row92\" class=\"row_heading level0 row92\" >280</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col0\" class=\"data row92 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col1\" class=\"data row92 col1\" >76</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col2\" class=\"data row92 col2\" >828129</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col3\" class=\"data row92 col3\" >935833</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col4\" class=\"data row92 col4\" >107704</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col5\" class=\"data row92 col5\" >13.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row93\" class=\"row_heading level0 row93\" >28</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col0\" class=\"data row93 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col1\" class=\"data row93 col1\" >28</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col2\" class=\"data row93 col2\" >4247541</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col3\" class=\"data row93 col3\" >4355240</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col4\" class=\"data row93 col4\" >107699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col5\" class=\"data row93 col5\" >2.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row94\" class=\"row_heading level0 row94\" >131</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col0\" class=\"data row94 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col1\" class=\"data row94 col1\" >29</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col2\" class=\"data row94 col2\" >2112313</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col3\" class=\"data row94 col3\" >2219872</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col4\" class=\"data row94 col4\" >107559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col5\" class=\"data row94 col5\" >5.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row95\" class=\"row_heading level0 row95\" >272</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col0\" class=\"data row95 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col1\" class=\"data row95 col1\" >68</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col2\" class=\"data row95 col2\" >1254117</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col3\" class=\"data row95 col3\" >1361081</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col4\" class=\"data row95 col4\" >106964</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col5\" class=\"data row95 col5\" >8.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row96\" class=\"row_heading level0 row96\" >77</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col0\" class=\"data row96 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col1\" class=\"data row96 col1\" >77</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col2\" class=\"data row96 col2\" >1449173</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col3\" class=\"data row96 col3\" >1556104</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col4\" class=\"data row96 col4\" >106931</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col5\" class=\"data row96 col5\" >7.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row97\" class=\"row_heading level0 row97\" >266</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col0\" class=\"data row97 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col1\" class=\"data row97 col1\" >62</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col2\" class=\"data row97 col2\" >1815999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col3\" class=\"data row97 col3\" >1922402</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col4\" class=\"data row97 col4\" >106403</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col5\" class=\"data row97 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row98\" class=\"row_heading level0 row98\" >170</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col0\" class=\"data row98 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col1\" class=\"data row98 col1\" >68</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col2\" class=\"data row98 col2\" >1105699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col3\" class=\"data row98 col3\" >1211278</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col4\" class=\"data row98 col4\" >105579</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col5\" class=\"data row98 col5\" >9.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row99\" class=\"row_heading level0 row99\" >278</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col0\" class=\"data row99 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col1\" class=\"data row99 col1\" >74</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col2\" class=\"data row99 col2\" >927165</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col3\" class=\"data row99 col3\" >1032543</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col4\" class=\"data row99 col4\" >105378</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col5\" class=\"data row99 col5\" >11.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row100\" class=\"row_heading level0 row100\" >21</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col0\" class=\"data row100 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col1\" class=\"data row100 col1\" >21</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col2\" class=\"data row100 col2\" >4387956</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col3\" class=\"data row100 col3\" >4492373</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col4\" class=\"data row100 col4\" >104417</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col5\" class=\"data row100 col5\" >2.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row101\" class=\"row_heading level0 row101\" >178</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col0\" class=\"data row101 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col1\" class=\"data row101 col1\" >76</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col2\" class=\"data row101 col2\" >653551</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col3\" class=\"data row101 col3\" >757841</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col4\" class=\"data row101 col4\" >104290</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col5\" class=\"data row101 col5\" >15.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row102\" class=\"row_heading level0 row102\" >229</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col0\" class=\"data row102 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col1\" class=\"data row102 col1\" >25</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col2\" class=\"data row102 col2\" >2112297</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col3\" class=\"data row102 col3\" >2214495</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col4\" class=\"data row102 col4\" >102198</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col5\" class=\"data row102 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row103\" class=\"row_heading level0 row103\" >248</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col0\" class=\"data row103 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col1\" class=\"data row103 col1\" >44</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col2\" class=\"data row103 col2\" >2103936</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col3\" class=\"data row103 col3\" >2205835</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col4\" class=\"data row103 col4\" >101899</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col5\" class=\"data row103 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row104\" class=\"row_heading level0 row104\" >138</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col0\" class=\"data row104 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col1\" class=\"data row104 col1\" >36</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col2\" class=\"data row104 col2\" >1907408</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col3\" class=\"data row104 col3\" >2005880</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col4\" class=\"data row104 col4\" >98472</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col5\" class=\"data row104 col5\" >5.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row105\" class=\"row_heading level0 row105\" >176</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col0\" class=\"data row105 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col1\" class=\"data row105 col1\" >74</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col2\" class=\"data row105 col2\" >758830</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col3\" class=\"data row105 col3\" >856970</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col4\" class=\"data row105 col4\" >98140</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col5\" class=\"data row105 col5\" >12.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row106\" class=\"row_heading level0 row106\" >27</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col0\" class=\"data row106 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col1\" class=\"data row106 col1\" >27</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col2\" class=\"data row106 col2\" >4237026</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col3\" class=\"data row106 col3\" >4334806</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col4\" class=\"data row106 col4\" >97780</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col5\" class=\"data row106 col5\" >2.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row107\" class=\"row_heading level0 row107\" >53</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col0\" class=\"data row107 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col1\" class=\"data row107 col1\" >53</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col2\" class=\"data row107 col2\" >4439403</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col3\" class=\"data row107 col3\" >4535430</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col4\" class=\"data row107 col4\" >96027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col5\" class=\"data row107 col5\" >2.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row108\" class=\"row_heading level0 row108\" >8</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col0\" class=\"data row108 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col1\" class=\"data row108 col1\" >8</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col2\" class=\"data row108 col2\" >4025604</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col3\" class=\"data row108 col3\" >4120903</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col4\" class=\"data row108 col4\" >95299</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col5\" class=\"data row108 col5\" >2.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row109\" class=\"row_heading level0 row109\" >14</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col0\" class=\"data row109 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col1\" class=\"data row109 col1\" >14</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col2\" class=\"data row109 col2\" >4145614</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col3\" class=\"data row109 col3\" >4233839</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col4\" class=\"data row109 col4\" >88225</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col5\" class=\"data row109 col5\" >2.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row110\" class=\"row_heading level0 row110\" >240</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col0\" class=\"data row110 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col1\" class=\"data row110 col1\" >36</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col2\" class=\"data row110 col2\" >1922791</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col3\" class=\"data row110 col3\" >2010831</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col4\" class=\"data row110 col4\" >88040</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col5\" class=\"data row110 col5\" >4.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row111\" class=\"row_heading level0 row111\" >164</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col0\" class=\"data row111 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col1\" class=\"data row111 col1\" >62</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col2\" class=\"data row111 col2\" >1679060</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col3\" class=\"data row111 col3\" >1762880</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col4\" class=\"data row111 col4\" >83820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col5\" class=\"data row111 col5\" >4.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row112\" class=\"row_heading level0 row112\" >157</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col0\" class=\"data row112 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col1\" class=\"data row112 col1\" >55</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col2\" class=\"data row112 col2\" >2075199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col3\" class=\"data row112 col3\" >2158427</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col4\" class=\"data row112 col4\" >83228</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col5\" class=\"data row112 col5\" >4.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row113\" class=\"row_heading level0 row113\" >91</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col0\" class=\"data row113 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col1\" class=\"data row113 col1\" >91</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col2\" class=\"data row113 col2\" >344442</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col3\" class=\"data row113 col3\" >425314</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col4\" class=\"data row113 col4\" >80872</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col5\" class=\"data row113 col5\" >23.48%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row114\" class=\"row_heading level0 row114\" >37</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col0\" class=\"data row114 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col1\" class=\"data row114 col1\" >37</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col2\" class=\"data row114 col2\" >3896766</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col3\" class=\"data row114 col3\" >3976750</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col4\" class=\"data row114 col4\" >79984</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col5\" class=\"data row114 col5\" >2.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row115\" class=\"row_heading level0 row115\" >259</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col0\" class=\"data row115 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col1\" class=\"data row115 col1\" >55</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col2\" class=\"data row115 col2\" >2183771</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col3\" class=\"data row115 col3\" >2263429</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col4\" class=\"data row115 col4\" >79658</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col5\" class=\"data row115 col5\" >3.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row116\" class=\"row_heading level0 row116\" >78</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col0\" class=\"data row116 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col1\" class=\"data row116 col1\" >78</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col2\" class=\"data row116 col2\" >1402182</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col3\" class=\"data row116 col3\" >1480611</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col4\" class=\"data row116 col4\" >78429</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col5\" class=\"data row116 col5\" >5.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row117\" class=\"row_heading level0 row117\" >177</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col0\" class=\"data row117 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col1\" class=\"data row117 col1\" >75</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col2\" class=\"data row117 col2\" >725663</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col3\" class=\"data row117 col3\" >802960</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col4\" class=\"data row117 col4\" >77297</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col5\" class=\"data row117 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row118\" class=\"row_heading level0 row118\" >239</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col0\" class=\"data row118 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col1\" class=\"data row118 col1\" >35</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col2\" class=\"data row118 col2\" >1973699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col3\" class=\"data row118 col3\" >2047905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col4\" class=\"data row118 col4\" >74206</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col5\" class=\"data row118 col5\" >3.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row119\" class=\"row_heading level0 row119\" >233</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col0\" class=\"data row119 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col1\" class=\"data row119 col1\" >29</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col2\" class=\"data row119 col2\" >2097973</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col3\" class=\"data row119 col3\" >2171916</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col4\" class=\"data row119 col4\" >73943</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col5\" class=\"data row119 col5\" >3.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row120\" class=\"row_heading level0 row120\" >130</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col0\" class=\"data row120 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col1\" class=\"data row120 col1\" >28</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col2\" class=\"data row120 col2\" >2134981</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col3\" class=\"data row120 col3\" >2208749</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col4\" class=\"data row120 col4\" >73768</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col5\" class=\"data row120 col5\" >3.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row121\" class=\"row_heading level0 row121\" >137</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col0\" class=\"data row121 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col1\" class=\"data row121 col1\" >35</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col2\" class=\"data row121 col2\" >1974636</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col3\" class=\"data row121 col3\" >2047877</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col4\" class=\"data row121 col4\" >73241</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col5\" class=\"data row121 col5\" >3.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row122\" class=\"row_heading level0 row122\" >123</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col0\" class=\"data row122 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col1\" class=\"data row122 col1\" >21</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col2\" class=\"data row122 col2\" >2241083</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col3\" class=\"data row122 col3\" >2312917</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col4\" class=\"data row122 col4\" >71834</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col5\" class=\"data row122 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row123\" class=\"row_heading level0 row123\" >129</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col0\" class=\"data row123 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col1\" class=\"data row123 col1\" >27</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col2\" class=\"data row123 col2\" >2135178</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col3\" class=\"data row123 col3\" >2201518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col4\" class=\"data row123 col4\" >66340</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col5\" class=\"data row123 col5\" >3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row124\" class=\"row_heading level0 row124\" >93</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col0\" class=\"data row124 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col1\" class=\"data row124 col1\" >93</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col2\" class=\"data row124 col2\" >219064</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col3\" class=\"data row124 col3\" >284885</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col4\" class=\"data row124 col4\" >65821</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col5\" class=\"data row124 col5\" >30.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row125\" class=\"row_heading level0 row125\" >279</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col0\" class=\"data row125 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col1\" class=\"data row125 col1\" >75</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col2\" class=\"data row125 col2\" >906215</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col3\" class=\"data row125 col3\" >970796</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col4\" class=\"data row125 col4\" >64581</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col5\" class=\"data row125 col5\" >7.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row126\" class=\"row_heading level0 row126\" >92</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col0\" class=\"data row126 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col1\" class=\"data row126 col1\" >92</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col2\" class=\"data row126 col2\" >288841</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col3\" class=\"data row126 col3\" >352912</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col4\" class=\"data row126 col4\" >64071</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col5\" class=\"data row126 col5\" >22.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row127\" class=\"row_heading level0 row127\" >6</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col0\" class=\"data row127 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col1\" class=\"data row127 col1\" >6</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col2\" class=\"data row127 col2\" >4073013</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col3\" class=\"data row127 col3\" >4135930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col4\" class=\"data row127 col4\" >62917</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col5\" class=\"data row127 col5\" >1.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row128\" class=\"row_heading level0 row128\" >90</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col0\" class=\"data row128 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col1\" class=\"data row128 col1\" >90</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col2\" class=\"data row128 col2\" >448324</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col3\" class=\"data row128 col3\" >511074</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col4\" class=\"data row128 col4\" >62750</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col5\" class=\"data row128 col5\" >14.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row129\" class=\"row_heading level0 row129\" >109</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col0\" class=\"data row129 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col1\" class=\"data row129 col1\" >7</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col2\" class=\"data row129 col2\" >2063139</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col3\" class=\"data row129 col3\" >2122832</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col4\" class=\"data row129 col4\" >59693</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col5\" class=\"data row129 col5\" >2.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row130\" class=\"row_heading level0 row130\" >179</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col0\" class=\"data row130 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col1\" class=\"data row130 col1\" >77</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col2\" class=\"data row130 col2\" >630867</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col3\" class=\"data row130 col3\" >689162</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col4\" class=\"data row130 col4\" >58295</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col5\" class=\"data row130 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row131\" class=\"row_heading level0 row131\" >79</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col0\" class=\"data row131 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col1\" class=\"data row131 col1\" >79</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col2\" class=\"data row131 col2\" >1354912</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col3\" class=\"data row131 col3\" >1413193</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col4\" class=\"data row131 col4\" >58281</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col5\" class=\"data row131 col5\" >4.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row132\" class=\"row_heading level0 row132\" >211</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col0\" class=\"data row132 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col1\" class=\"data row132 col1\" >7</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col2\" class=\"data row132 col2\" >1979907</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col3\" class=\"data row132 col3\" >2032494</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col4\" class=\"data row132 col4\" >52587</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col5\" class=\"data row132 col5\" >2.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row133\" class=\"row_heading level0 row133\" >89</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col0\" class=\"data row133 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col1\" class=\"data row133 col1\" >89</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col2\" class=\"data row133 col2\" >546193</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col3\" class=\"data row133 col3\" >597828</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col4\" class=\"data row133 col4\" >51635</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col5\" class=\"data row133 col5\" >9.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row134\" class=\"row_heading level0 row134\" >13</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col0\" class=\"data row134 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col1\" class=\"data row134 col1\" >13</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col2\" class=\"data row134 col2\" >4119666</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col3\" class=\"data row134 col3\" >4171030</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col4\" class=\"data row134 col4\" >51364</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col5\" class=\"data row134 col5\" >1.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row135\" class=\"row_heading level0 row135\" >110</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col0\" class=\"data row135 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col1\" class=\"data row135 col1\" >8</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col2\" class=\"data row135 col2\" >2054462</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col3\" class=\"data row135 col3\" >2105618</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col4\" class=\"data row135 col4\" >51156</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col5\" class=\"data row135 col5\" >2.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row136\" class=\"row_heading level0 row136\" >281</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col0\" class=\"data row136 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col1\" class=\"data row136 col1\" >77</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col2\" class=\"data row136 col2\" >818306</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col3\" class=\"data row136 col3\" >866942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col4\" class=\"data row136 col4\" >48636</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col5\" class=\"data row136 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row137\" class=\"row_heading level0 row137\" >155</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col0\" class=\"data row137 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col1\" class=\"data row137 col1\" >53</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col2\" class=\"data row137 col2\" >2170923</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col3\" class=\"data row137 col3\" >2219328</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col4\" class=\"data row137 col4\" >48405</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col5\" class=\"data row137 col5\" >2.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row138\" class=\"row_heading level0 row138\" >295</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col0\" class=\"data row138 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col1\" class=\"data row138 col1\" >91</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col2\" class=\"data row138 col2\" >240151</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col3\" class=\"data row138 col3\" >287889</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col4\" class=\"data row138 col4\" >47738</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col5\" class=\"data row138 col5\" >19.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row139\" class=\"row_heading level0 row139\" >257</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col0\" class=\"data row139 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col1\" class=\"data row139 col1\" >53</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col2\" class=\"data row139 col2\" >2268480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col3\" class=\"data row139 col3\" >2316102</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col4\" class=\"data row139 col4\" >47622</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col5\" class=\"data row139 col5\" >2.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row140\" class=\"row_heading level0 row140\" >87</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col0\" class=\"data row140 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col1\" class=\"data row140 col1\" >87</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col2\" class=\"data row140 col2\" >721196</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col3\" class=\"data row140 col3\" >768676</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col4\" class=\"data row140 col4\" >47480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col5\" class=\"data row140 col5\" >6.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row141\" class=\"row_heading level0 row141\" >84</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col0\" class=\"data row141 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col1\" class=\"data row141 col1\" >84</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col2\" class=\"data row141 col2\" >987023</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col3\" class=\"data row141 col3\" >1034369</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col4\" class=\"data row141 col4\" >47346</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col5\" class=\"data row141 col5\" >4.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row142\" class=\"row_heading level0 row142\" >94</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col0\" class=\"data row142 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col1\" class=\"data row142 col1\" >94</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col2\" class=\"data row142 col2\" >170775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col3\" class=\"data row142 col3\" >217328</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col4\" class=\"data row142 col4\" >46553</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col5\" class=\"data row142 col5\" >27.26%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row143\" class=\"row_heading level0 row143\" >218</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col0\" class=\"data row143 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col1\" class=\"data row143 col1\" >14</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col2\" class=\"data row143 col2\" >2022701</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col3\" class=\"data row143 col3\" >2068915</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col4\" class=\"data row143 col4\" >46214</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col5\" class=\"data row143 col5\" >2.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row144\" class=\"row_heading level0 row144\" >180</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col0\" class=\"data row144 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col1\" class=\"data row144 col1\" >78</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col2\" class=\"data row144 col2\" >602774</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col3\" class=\"data row144 col3\" >648696</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col4\" class=\"data row144 col4\" >45922</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col5\" class=\"data row144 col5\" >7.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row145\" class=\"row_heading level0 row145\" >139</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col0\" class=\"data row145 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col1\" class=\"data row145 col1\" >37</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col2\" class=\"data row145 col2\" >1934537</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col3\" class=\"data row145 col3\" >1979888</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col4\" class=\"data row145 col4\" >45351</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col5\" class=\"data row145 col5\" >2.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row146\" class=\"row_heading level0 row146\" >212</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col0\" class=\"data row146 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col1\" class=\"data row146 col1\" >8</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col2\" class=\"data row146 col2\" >1971142</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col3\" class=\"data row146 col3\" >2015285</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col4\" class=\"data row146 col4\" >44143</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col5\" class=\"data row146 col5\" >2.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row147\" class=\"row_heading level0 row147\" >116</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col0\" class=\"data row147 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col1\" class=\"data row147 col1\" >14</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col2\" class=\"data row147 col2\" >2122913</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col3\" class=\"data row147 col3\" >2164924</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col4\" class=\"data row147 col4\" >42011</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col5\" class=\"data row147 col5\" >1.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row148\" class=\"row_heading level0 row148\" >297</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col0\" class=\"data row148 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col1\" class=\"data row148 col1\" >93</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col2\" class=\"data row148 col2\" >158882</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col3\" class=\"data row148 col3\" >199426</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col4\" class=\"data row148 col4\" >40544</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col5\" class=\"data row148 col5\" >25.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row149\" class=\"row_heading level0 row149\" >296</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col0\" class=\"data row149 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col1\" class=\"data row149 col1\" >92</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col2\" class=\"data row149 col2\" >205379</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col3\" class=\"data row149 col3\" >243648</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col4\" class=\"data row149 col4\" >38269</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col5\" class=\"data row149 col5\" >18.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row150\" class=\"row_heading level0 row150\" >88</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col0\" class=\"data row150 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col1\" class=\"data row150 col1\" >88</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col2\" class=\"data row150 col2\" >636657</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col3\" class=\"data row150 col3\" >673402</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col4\" class=\"data row150 col4\" >36745</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col5\" class=\"data row150 col5\" >5.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row151\" class=\"row_heading level0 row151\" >181</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col0\" class=\"data row151 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col1\" class=\"data row151 col1\" >79</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col2\" class=\"data row151 col2\" >573885</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col3\" class=\"data row151 col3\" >610115</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col4\" class=\"data row151 col4\" >36230</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col5\" class=\"data row151 col5\" >6.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row152\" class=\"row_heading level0 row152\" >186</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col0\" class=\"data row152 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col1\" class=\"data row152 col1\" >84</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col2\" class=\"data row152 col2\" >375685</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col3\" class=\"data row152 col3\" >410385</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col4\" class=\"data row152 col4\" >34700</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col5\" class=\"data row152 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row153\" class=\"row_heading level0 row153\" >241</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col0\" class=\"data row153 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col1\" class=\"data row153 col1\" >37</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col2\" class=\"data row153 col2\" >1962229</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col3\" class=\"data row153 col3\" >1996862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col4\" class=\"data row153 col4\" >34633</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col5\" class=\"data row153 col5\" >1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row154\" class=\"row_heading level0 row154\" >294</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col0\" class=\"data row154 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col1\" class=\"data row154 col1\" >90</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col2\" class=\"data row154 col2\" >306925</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col3\" class=\"data row154 col3\" >341430</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col4\" class=\"data row154 col4\" >34505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col5\" class=\"data row154 col5\" >11.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row155\" class=\"row_heading level0 row155\" >232</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col0\" class=\"data row155 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col1\" class=\"data row155 col1\" >28</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col2\" class=\"data row155 col2\" >2112560</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col3\" class=\"data row155 col3\" >2146491</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col4\" class=\"data row155 col4\" >33931</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col5\" class=\"data row155 col5\" >1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row156\" class=\"row_heading level0 row156\" >193</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col0\" class=\"data row156 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col1\" class=\"data row156 col1\" >91</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col2\" class=\"data row156 col2\" >104291</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col3\" class=\"data row156 col3\" >137425</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col4\" class=\"data row156 col4\" >33134</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col5\" class=\"data row156 col5\" >31.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row157\" class=\"row_heading level0 row157\" >225</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col0\" class=\"data row157 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col1\" class=\"data row157 col1\" >21</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col2\" class=\"data row157 col2\" >2146873</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col3\" class=\"data row157 col3\" >2179456</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col4\" class=\"data row157 col4\" >32583</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col5\" class=\"data row157 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row158\" class=\"row_heading level0 row158\" >282</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col0\" class=\"data row158 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col1\" class=\"data row158 col1\" >78</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col2\" class=\"data row158 col2\" >799408</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col3\" class=\"data row158 col3\" >831915</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col4\" class=\"data row158 col4\" >32507</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col5\" class=\"data row158 col5\" >4.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row159\" class=\"row_heading level0 row159\" >86</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col0\" class=\"data row159 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col1\" class=\"data row159 col1\" >86</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col2\" class=\"data row159 col2\" >821549</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col3\" class=\"data row159 col3\" >853723</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col4\" class=\"data row159 col4\" >32174</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col5\" class=\"data row159 col5\" >3.92%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row160\" class=\"row_heading level0 row160\" >108</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col0\" class=\"data row160 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col1\" class=\"data row160 col1\" >6</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col2\" class=\"data row160 col2\" >2079410</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col3\" class=\"data row160 col3\" >2111060</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col4\" class=\"data row160 col4\" >31650</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col5\" class=\"data row160 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row161\" class=\"row_heading level0 row161\" >231</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col0\" class=\"data row161 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col1\" class=\"data row161 col1\" >27</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col2\" class=\"data row161 col2\" >2101848</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col3\" class=\"data row161 col3\" >2133288</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col4\" class=\"data row161 col4\" >31440</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col5\" class=\"data row161 col5\" >1.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row162\" class=\"row_heading level0 row162\" >210</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col0\" class=\"data row162 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col1\" class=\"data row162 col1\" >6</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col2\" class=\"data row162 col2\" >1993603</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col3\" class=\"data row162 col3\" >2024870</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col4\" class=\"data row162 col4\" >31267</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col5\" class=\"data row162 col5\" >1.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row163\" class=\"row_heading level0 row163\" >189</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col0\" class=\"data row163 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col1\" class=\"data row163 col1\" >87</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col2\" class=\"data row163 col2\" >253621</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col3\" class=\"data row163 col3\" >282423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col4\" class=\"data row163 col4\" >28802</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col5\" class=\"data row163 col5\" >11.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row164\" class=\"row_heading level0 row164\" >298</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col0\" class=\"data row164 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col1\" class=\"data row164 col1\" >94</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col2\" class=\"data row164 col2\" >126948</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col3\" class=\"data row164 col3\" >155637</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col4\" class=\"data row164 col4\" >28689</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col5\" class=\"data row164 col5\" >22.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row165\" class=\"row_heading level0 row165\" >192</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col0\" class=\"data row165 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col1\" class=\"data row165 col1\" >90</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col2\" class=\"data row165 col2\" >141399</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col3\" class=\"data row165 col3\" >169644</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col4\" class=\"data row165 col4\" >28245</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col5\" class=\"data row165 col5\" >19.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row166\" class=\"row_heading level0 row166\" >217</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col0\" class=\"data row166 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col1\" class=\"data row166 col1\" >13</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col2\" class=\"data row166 col2\" >2014717</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col3\" class=\"data row166 col3\" >2042116</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col4\" class=\"data row166 col4\" >27399</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col5\" class=\"data row166 col5\" >1.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row167\" class=\"row_heading level0 row167\" >293</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col0\" class=\"data row167 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col1\" class=\"data row167 col1\" >89</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col2\" class=\"data row167 col2\" >365732</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col3\" class=\"data row167 col3\" >392978</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col4\" class=\"data row167 col4\" >27246</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col5\" class=\"data row167 col5\" >7.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row168\" class=\"row_heading level0 row168\" >188</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col0\" class=\"data row168 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col1\" class=\"data row168 col1\" >86</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col2\" class=\"data row168 col2\" >295396</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col3\" class=\"data row168 col3\" >322043</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col4\" class=\"data row168 col4\" >26647</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col5\" class=\"data row168 col5\" >9.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row169\" class=\"row_heading level0 row169\" >194</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col0\" class=\"data row169 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col1\" class=\"data row169 col1\" >92</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col2\" class=\"data row169 col2\" >83462</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col3\" class=\"data row169 col3\" >109264</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col4\" class=\"data row169 col4\" >25802</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col5\" class=\"data row169 col5\" >30.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row170\" class=\"row_heading level0 row170\" >195</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col0\" class=\"data row170 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col1\" class=\"data row170 col1\" >93</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col2\" class=\"data row170 col2\" >60182</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col3\" class=\"data row170 col3\" >85459</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col4\" class=\"data row170 col4\" >25277</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col5\" class=\"data row170 col5\" >42.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row171\" class=\"row_heading level0 row171\" >95</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col0\" class=\"data row171 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col1\" class=\"data row171 col1\" >95</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col2\" class=\"data row171 col2\" >131077</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col3\" class=\"data row171 col3\" >156288</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col4\" class=\"data row171 col4\" >25211</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col5\" class=\"data row171 col5\" >19.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row172\" class=\"row_heading level0 row172\" >191</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col0\" class=\"data row172 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col1\" class=\"data row172 col1\" >89</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col2\" class=\"data row172 col2\" >180461</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col3\" class=\"data row172 col3\" >204850</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col4\" class=\"data row172 col4\" >24389</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col5\" class=\"data row172 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row173\" class=\"row_heading level0 row173\" >115</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col0\" class=\"data row173 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col1\" class=\"data row173 col1\" >13</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col2\" class=\"data row173 col2\" >2104949</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col3\" class=\"data row173 col3\" >2128914</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col4\" class=\"data row173 col4\" >23965</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col5\" class=\"data row173 col5\" >1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row174\" class=\"row_heading level0 row174\" >96</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col0\" class=\"data row174 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col1\" class=\"data row174 col1\" >96</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col2\" class=\"data row174 col2\" >97161</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col3\" class=\"data row174 col3\" >120485</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col4\" class=\"data row174 col4\" >23324</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col5\" class=\"data row174 col5\" >24.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row175\" class=\"row_heading level0 row175\" >190</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col0\" class=\"data row175 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col1\" class=\"data row175 col1\" >88</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col2\" class=\"data row175 col2\" >216220</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col3\" class=\"data row175 col3\" >239455</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col4\" class=\"data row175 col4\" >23235</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col5\" class=\"data row175 col5\" >10.75%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row176\" class=\"row_heading level0 row176\" >283</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col0\" class=\"data row176 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col1\" class=\"data row176 col1\" >79</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col2\" class=\"data row176 col2\" >781027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col3\" class=\"data row176 col3\" >803078</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col4\" class=\"data row176 col4\" >22051</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col5\" class=\"data row176 col5\" >2.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row177\" class=\"row_heading level0 row177\" >187</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col0\" class=\"data row177 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col1\" class=\"data row177 col1\" >85</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col2\" class=\"data row177 col2\" >337661</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col3\" class=\"data row177 col3\" >358342</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col4\" class=\"data row177 col4\" >20681</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col5\" class=\"data row177 col5\" >6.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row178\" class=\"row_heading level0 row178\" >291</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col0\" class=\"data row178 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col1\" class=\"data row178 col1\" >87</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col2\" class=\"data row178 col2\" >467575</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col3\" class=\"data row178 col3\" >486253</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col4\" class=\"data row178 col4\" >18678</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col5\" class=\"data row178 col5\" >3.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row179\" class=\"row_heading level0 row179\" >185</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col0\" class=\"data row179 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col1\" class=\"data row179 col1\" >83</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col2\" class=\"data row179 col2\" >422999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col3\" class=\"data row179 col3\" >441530</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col4\" class=\"data row179 col4\" >18531</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col5\" class=\"data row179 col5\" >4.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row180\" class=\"row_heading level0 row180\" >196</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col0\" class=\"data row180 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col1\" class=\"data row180 col1\" >94</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col2\" class=\"data row180 col2\" >43827</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col3\" class=\"data row180 col3\" >61691</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col4\" class=\"data row180 col4\" >17864</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col5\" class=\"data row180 col5\" >40.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row181\" class=\"row_heading level0 row181\" >100</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col0\" class=\"data row181 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col1\" class=\"data row181 col1\" >100</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col2\" class=\"data row181 col2\" >54410</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col3\" class=\"data row181 col3\" >71626</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col4\" class=\"data row181 col4\" >17216</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col5\" class=\"data row181 col5\" >31.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row182\" class=\"row_heading level0 row182\" >42</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col0\" class=\"data row182 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col1\" class=\"data row182 col1\" >42</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col2\" class=\"data row182 col2\" >4082712</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col3\" class=\"data row182 col3\" >4097698</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col4\" class=\"data row182 col4\" >14986</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col5\" class=\"data row182 col5\" >0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row183\" class=\"row_heading level0 row183\" >246</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col0\" class=\"data row183 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col1\" class=\"data row183 col1\" >42</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col2\" class=\"data row183 col2\" >2050930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col3\" class=\"data row183 col3\" >2065491</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col4\" class=\"data row183 col4\" >14561</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col5\" class=\"data row183 col5\" >0.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row184\" class=\"row_heading level0 row184\" >299</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col0\" class=\"data row184 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col1\" class=\"data row184 col1\" >95</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col2\" class=\"data row184 col2\" >99341</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col3\" class=\"data row184 col3\" >113732</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col4\" class=\"data row184 col4\" >14391</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col5\" class=\"data row184 col5\" >14.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row185\" class=\"row_heading level0 row185\" >300</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col0\" class=\"data row185 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col1\" class=\"data row185 col1\" >96</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col2\" class=\"data row185 col2\" >75139</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col3\" class=\"data row185 col3\" >89432</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col4\" class=\"data row185 col4\" >14293</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col5\" class=\"data row185 col5\" >19.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row186\" class=\"row_heading level0 row186\" >183</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col0\" class=\"data row186 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col1\" class=\"data row186 col1\" >81</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col2\" class=\"data row186 col2\" >496070</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col3\" class=\"data row186 col3\" >510305</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col4\" class=\"data row186 col4\" >14235</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col5\" class=\"data row186 col5\" >2.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row187\" class=\"row_heading level0 row187\" >97</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col0\" class=\"data row187 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col1\" class=\"data row187 col1\" >97</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col2\" class=\"data row187 col2\" >68893</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col3\" class=\"data row187 col3\" >83089</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col4\" class=\"data row187 col4\" >14196</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col5\" class=\"data row187 col5\" >20.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row188\" class=\"row_heading level0 row188\" >292</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col0\" class=\"data row188 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col1\" class=\"data row188 col1\" >88</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col2\" class=\"data row188 col2\" >420437</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col3\" class=\"data row188 col3\" >433947</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col4\" class=\"data row188 col4\" >13510</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col5\" class=\"data row188 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row189\" class=\"row_heading level0 row189\" >184</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col0\" class=\"data row189 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col1\" class=\"data row189 col1\" >82</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col2\" class=\"data row189 col2\" >462807</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col3\" class=\"data row189 col3\" >476034</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col4\" class=\"data row189 col4\" >13227</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col5\" class=\"data row189 col5\" >2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row190\" class=\"row_heading level0 row190\" >304</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col0\" class=\"data row190 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col1\" class=\"data row190 col1\" >100</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col2\" class=\"data row190 col2\" >45058</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col3\" class=\"data row190 col3\" >58008</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col4\" class=\"data row190 col4\" >12950</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col5\" class=\"data row190 col5\" >28.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row191\" class=\"row_heading level0 row191\" >98</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col0\" class=\"data row191 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col1\" class=\"data row191 col1\" >98</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col2\" class=\"data row191 col2\" >47037</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col3\" class=\"data row191 col3\" >59726</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col4\" class=\"data row191 col4\" >12689</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col5\" class=\"data row191 col5\" >26.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row192\" class=\"row_heading level0 row192\" >288</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col0\" class=\"data row192 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col1\" class=\"data row192 col1\" >84</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col2\" class=\"data row192 col2\" >611338</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col3\" class=\"data row192 col3\" >623984</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col4\" class=\"data row192 col4\" >12646</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col5\" class=\"data row192 col5\" >2.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row193\" class=\"row_heading level0 row193\" >197</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col0\" class=\"data row193 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col1\" class=\"data row193 col1\" >95</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col2\" class=\"data row193 col2\" >31736</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col3\" class=\"data row193 col3\" >42556</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col4\" class=\"data row193 col4\" >10820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col5\" class=\"data row193 col5\" >34.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row194\" class=\"row_heading level0 row194\" >99</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col0\" class=\"data row194 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col1\" class=\"data row194 col1\" >99</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col2\" class=\"data row194 col2\" >32178</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col3\" class=\"data row194 col3\" >41468</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col4\" class=\"data row194 col4\" >9290</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col5\" class=\"data row194 col5\" >28.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row195\" class=\"row_heading level0 row195\" >198</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col0\" class=\"data row195 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col1\" class=\"data row195 col1\" >96</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col2\" class=\"data row195 col2\" >22022</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col3\" class=\"data row195 col3\" >31053</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col4\" class=\"data row195 col4\" >9031</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col5\" class=\"data row195 col5\" >41.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row196\" class=\"row_heading level0 row196\" >302</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col0\" class=\"data row196 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col1\" class=\"data row196 col1\" >98</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col2\" class=\"data row196 col2\" >37532</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col3\" class=\"data row196 col3\" >46208</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col4\" class=\"data row196 col4\" >8676</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col5\" class=\"data row196 col5\" >23.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row197\" class=\"row_heading level0 row197\" >301</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col0\" class=\"data row197 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col1\" class=\"data row197 col1\" >97</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col2\" class=\"data row197 col2\" >54118</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col3\" class=\"data row197 col3\" >62779</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col4\" class=\"data row197 col4\" >8661</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col5\" class=\"data row197 col5\" >16.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row198\" class=\"row_heading level0 row198\" >85</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col0\" class=\"data row198 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col1\" class=\"data row198 col1\" >85</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col2\" class=\"data row198 col2\" >915013</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col3\" class=\"data row198 col3\" >922947</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col4\" class=\"data row198 col4\" >7934</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col5\" class=\"data row198 col5\" >0.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row199\" class=\"row_heading level0 row199\" >83</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col0\" class=\"data row199 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col1\" class=\"data row199 col1\" >83</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col2\" class=\"data row199 col2\" >1081440</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col3\" class=\"data row199 col3\" >1088601</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col4\" class=\"data row199 col4\" >7161</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col5\" class=\"data row199 col5\" >0.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row200\" class=\"row_heading level0 row200\" >303</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col0\" class=\"data row200 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col1\" class=\"data row200 col1\" >99</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col2\" class=\"data row200 col2\" >26074</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col3\" class=\"data row200 col3\" >32517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col4\" class=\"data row200 col4\" >6443</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col5\" class=\"data row200 col5\" >24.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row201\" class=\"row_heading level0 row201\" >199</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col0\" class=\"data row201 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col1\" class=\"data row201 col1\" >97</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col2\" class=\"data row201 col2\" >14775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col3\" class=\"data row201 col3\" >20310</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col4\" class=\"data row201 col4\" >5535</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col5\" class=\"data row201 col5\" >37.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row202\" class=\"row_heading level0 row202\" >290</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col0\" class=\"data row202 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col1\" class=\"data row202 col1\" >86</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col2\" class=\"data row202 col2\" >526153</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col3\" class=\"data row202 col3\" >531680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col4\" class=\"data row202 col4\" >5527</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col5\" class=\"data row202 col5\" >1.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row203\" class=\"row_heading level0 row203\" >202</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col0\" class=\"data row203 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col1\" class=\"data row203 col1\" >100</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col2\" class=\"data row203 col2\" >9352</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col3\" class=\"data row203 col3\" >13618</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col4\" class=\"data row203 col4\" >4266</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col5\" class=\"data row203 col5\" >45.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row204\" class=\"row_heading level0 row204\" >200</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col0\" class=\"data row204 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col1\" class=\"data row204 col1\" >98</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col2\" class=\"data row204 col2\" >9505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col3\" class=\"data row204 col3\" >13518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col4\" class=\"data row204 col4\" >4013</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col5\" class=\"data row204 col5\" >42.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row205\" class=\"row_heading level0 row205\" >201</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col0\" class=\"data row205 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col1\" class=\"data row205 col1\" >99</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col2\" class=\"data row205 col2\" >6104</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col3\" class=\"data row205 col3\" >8951</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col4\" class=\"data row205 col4\" >2847</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col5\" class=\"data row205 col5\" >46.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row206\" class=\"row_heading level0 row206\" >102</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col0\" class=\"data row206 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col1\" class=\"data row206 col1\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col2\" class=\"data row206 col2\" >2018420</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col3\" class=\"data row206 col3\" >2020326</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col4\" class=\"data row206 col4\" >1906</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col5\" class=\"data row206 col5\" >0.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row207\" class=\"row_heading level0 row207\" >81</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col0\" class=\"data row207 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col1\" class=\"data row207 col1\" >81</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col2\" class=\"data row207 col2\" >1212603</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col3\" class=\"data row207 col3\" >1214357</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col4\" class=\"data row207 col4\" >1754</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col5\" class=\"data row207 col5\" >0.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row208\" class=\"row_heading level0 row208\" >154</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col0\" class=\"data row208 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col1\" class=\"data row208 col1\" >52</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col2\" class=\"data row208 col2\" >2197161</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col3\" class=\"data row208 col3\" >2197801</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col4\" class=\"data row208 col4\" >640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col5\" class=\"data row208 col5\" >0.03%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row209\" class=\"row_heading level0 row209\" >144</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col0\" class=\"data row209 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col1\" class=\"data row209 col1\" >42</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col2\" class=\"data row209 col2\" >2031782</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col3\" class=\"data row209 col3\" >2032207</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col4\" class=\"data row209 col4\" >425</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col5\" class=\"data row209 col5\" >0.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row210\" class=\"row_heading level0 row210\" >52</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col0\" class=\"data row210 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col1\" class=\"data row210 col1\" >52</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col2\" class=\"data row210 col2\" >4480584</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col3\" class=\"data row210 col3\" >4480188</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col4\" class=\"data row210 col4\" >-396</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col5\" class=\"data row210 col5\" >-0.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row211\" class=\"row_heading level0 row211\" >256</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col0\" class=\"data row211 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col1\" class=\"data row211 col1\" >52</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col2\" class=\"data row211 col2\" >2283423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col3\" class=\"data row211 col3\" >2282387</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col4\" class=\"data row211 col4\" >-1036</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col5\" class=\"data row211 col5\" >-0.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row212\" class=\"row_heading level0 row212\" >0</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col0\" class=\"data row212 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col1\" class=\"data row212 col1\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col2\" class=\"data row212 col2\" >3951330</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col3\" class=\"data row212 col3\" >3949775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col4\" class=\"data row212 col4\" >-1555</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col5\" class=\"data row212 col5\" >-0.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row213\" class=\"row_heading level0 row213\" >103</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col0\" class=\"data row213 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col1\" class=\"data row213 col1\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col2\" class=\"data row213 col2\" >2020332</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col3\" class=\"data row213 col3\" >2018401</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col4\" class=\"data row213 col4\" >-1931</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col5\" class=\"data row213 col5\" >-0.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row214\" class=\"row_heading level0 row214\" >204</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col0\" class=\"data row214 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col1\" class=\"data row214 col1\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col2\" class=\"data row214 col2\" >1932910</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col3\" class=\"data row214 col3\" >1929449</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col4\" class=\"data row214 col4\" >-3461</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col5\" class=\"data row214 col5\" >-0.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row215\" class=\"row_heading level0 row215\" >153</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col0\" class=\"data row215 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col1\" class=\"data row215 col1\" >51</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col2\" class=\"data row215 col2\" >2209780</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col3\" class=\"data row215 col3\" >2205399</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col4\" class=\"data row215 col4\" >-4381</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col5\" class=\"data row215 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row216\" class=\"row_heading level0 row216\" >255</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col0\" class=\"data row216 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col1\" class=\"data row216 col1\" >51</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col2\" class=\"data row216 col2\" >2289194</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col3\" class=\"data row216 col3\" >2283994</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col4\" class=\"data row216 col4\" >-5200</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col5\" class=\"data row216 col5\" >-0.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row217\" class=\"row_heading level0 row217\" >205</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col0\" class=\"data row217 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col1\" class=\"data row217 col1\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col2\" class=\"data row217 col2\" >1937556</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col3\" class=\"data row217 col3\" >1931375</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col4\" class=\"data row217 col4\" >-6181</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col5\" class=\"data row217 col5\" >-0.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row218\" class=\"row_heading level0 row218\" >82</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col0\" class=\"data row218 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col1\" class=\"data row218 col1\" >82</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col2\" class=\"data row218 col2\" >1158351</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col3\" class=\"data row218 col3\" >1151677</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col4\" class=\"data row218 col4\" >-6674</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col5\" class=\"data row218 col5\" >-0.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row219\" class=\"row_heading level0 row219\" >215</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col0\" class=\"data row219 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col1\" class=\"data row219 col1\" >11</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col2\" class=\"data row219 col2\" >2010714</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col3\" class=\"data row219 col3\" >2003233</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col4\" class=\"data row219 col4\" >-7481</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col5\" class=\"data row219 col5\" >-0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row220\" class=\"row_heading level0 row220\" >213</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col0\" class=\"data row220 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col1\" class=\"data row220 col1\" >9</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col2\" class=\"data row220 col2\" >2018378</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col3\" class=\"data row220 col3\" >2010659</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col4\" class=\"data row220 col4\" >-7719</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col5\" class=\"data row220 col5\" >-0.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row221\" class=\"row_heading level0 row221\" >1</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col0\" class=\"data row221 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col1\" class=\"data row221 col1\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col2\" class=\"data row221 col2\" >3957888</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col3\" class=\"data row221 col3\" >3949776</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col4\" class=\"data row221 col4\" >-8112</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col5\" class=\"data row221 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row222\" class=\"row_heading level0 row222\" >111</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col0\" class=\"data row222 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col1\" class=\"data row222 col1\" >9</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col2\" class=\"data row222 col2\" >2107037</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col3\" class=\"data row222 col3\" >2097690</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col4\" class=\"data row222 col4\" >-9347</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col5\" class=\"data row222 col5\" >-0.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row223\" class=\"row_heading level0 row223\" >51</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col0\" class=\"data row223 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col1\" class=\"data row223 col1\" >51</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col2\" class=\"data row223 col2\" >4498974</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col3\" class=\"data row223 col3\" >4489393</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col4\" class=\"data row223 col4\" >-9581</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col5\" class=\"data row223 col5\" >-0.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row224\" class=\"row_heading level0 row224\" >182</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col0\" class=\"data row224 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col1\" class=\"data row224 col1\" >80</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col2\" class=\"data row224 col2\" >549216</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col3\" class=\"data row224 col3\" >539227</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col4\" class=\"data row224 col4\" >-9989</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col5\" class=\"data row224 col5\" >-1.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row225\" class=\"row_heading level0 row225\" >287</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col0\" class=\"data row225 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col1\" class=\"data row225 col1\" >83</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col2\" class=\"data row225 col2\" >658441</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col3\" class=\"data row225 col3\" >647071</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col4\" class=\"data row225 col4\" >-11370</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col5\" class=\"data row225 col5\" >-1.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row226\" class=\"row_heading level0 row226\" >285</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col0\" class=\"data row226 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col1\" class=\"data row226 col1\" >81</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col2\" class=\"data row226 col2\" >716533</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col3\" class=\"data row226 col3\" >704052</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col4\" class=\"data row226 col4\" >-12481</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col5\" class=\"data row226 col5\" >-1.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row227\" class=\"row_heading level0 row227\" >289</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col0\" class=\"data row227 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col1\" class=\"data row227 col1\" >85</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col2\" class=\"data row227 col2\" >577352</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col3\" class=\"data row227 col3\" >564605</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col4\" class=\"data row227 col4\" >-12747</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col5\" class=\"data row227 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row228\" class=\"row_heading level0 row228\" >216</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col0\" class=\"data row228 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col1\" class=\"data row228 col1\" >12</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col2\" class=\"data row228 col2\" >2009630</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col3\" class=\"data row228 col3\" >1994846</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col4\" class=\"data row228 col4\" >-14784</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col5\" class=\"data row228 col5\" >-0.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row229\" class=\"row_heading level0 row229\" >9</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col0\" class=\"data row229 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col1\" class=\"data row229 col1\" >9</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col2\" class=\"data row229 col2\" >4125415</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col3\" class=\"data row229 col3\" >4108349</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col4\" class=\"data row229 col4\" >-17066</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col5\" class=\"data row229 col5\" >-0.41%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row230\" class=\"row_heading level0 row230\" >286</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col0\" class=\"data row230 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col1\" class=\"data row230 col1\" >82</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col2\" class=\"data row230 col2\" >695544</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col3\" class=\"data row230 col3\" >675643</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col4\" class=\"data row230 col4\" >-19901</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col5\" class=\"data row230 col5\" >-2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row231\" class=\"row_heading level0 row231\" >113</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col0\" class=\"data row231 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col1\" class=\"data row231 col1\" >11</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col2\" class=\"data row231 col2\" >2104797</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col3\" class=\"data row231 col3\" >2084169</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col4\" class=\"data row231 col4\" >-20628</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col5\" class=\"data row231 col5\" >-0.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row232\" class=\"row_heading level0 row232\" >234</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col0\" class=\"data row232 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col1\" class=\"data row232 col1\" >30</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col2\" class=\"data row232 col2\" >2136744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col3\" class=\"data row232 col3\" >2113094</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col4\" class=\"data row232 col4\" >-23650</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col5\" class=\"data row232 col5\" >-1.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row233\" class=\"row_heading level0 row233\" >219</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col0\" class=\"data row233 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col1\" class=\"data row233 col1\" >15</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col2\" class=\"data row233 col2\" >2060560</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col3\" class=\"data row233 col3\" >2035734</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col4\" class=\"data row233 col4\" >-24826</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col5\" class=\"data row233 col5\" >-1.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row234\" class=\"row_heading level0 row234\" >132</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col0\" class=\"data row234 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col1\" class=\"data row234 col1\" >30</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col2\" class=\"data row234 col2\" >2167495</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col3\" class=\"data row234 col3\" >2142240</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col4\" class=\"data row234 col4\" >-25255</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col5\" class=\"data row234 col5\" >-1.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row235\" class=\"row_heading level0 row235\" >209</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col0\" class=\"data row235 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col1\" class=\"data row235 col1\" >5</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col2\" class=\"data row235 col2\" >1988080</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col3\" class=\"data row235 col3\" >1962561</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col4\" class=\"data row235 col4\" >-25519</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col5\" class=\"data row235 col5\" >-1.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row236\" class=\"row_heading level0 row236\" >267</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col0\" class=\"data row236 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col1\" class=\"data row236 col1\" >63</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col2\" class=\"data row236 col2\" >1898264</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col3\" class=\"data row236 col3\" >1870596</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col4\" class=\"data row236 col4\" >-27668</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col5\" class=\"data row236 col5\" >-1.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row237\" class=\"row_heading level0 row237\" >114</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col0\" class=\"data row237 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col1\" class=\"data row237 col1\" >12</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col2\" class=\"data row237 col2\" >2103649</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col3\" class=\"data row237 col3\" >2075836</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col4\" class=\"data row237 col4\" >-27813</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col5\" class=\"data row237 col5\" >-1.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row238\" class=\"row_heading level0 row238\" >11</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col0\" class=\"data row238 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col1\" class=\"data row238 col1\" >11</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col2\" class=\"data row238 col2\" >4115511</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col3\" class=\"data row238 col3\" >4087402</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col4\" class=\"data row238 col4\" >-28109</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col5\" class=\"data row238 col5\" >-0.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row239\" class=\"row_heading level0 row239\" >214</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col0\" class=\"data row239 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col1\" class=\"data row239 col1\" >10</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col2\" class=\"data row239 col2\" >2044895</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col3\" class=\"data row239 col3\" >2016680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col4\" class=\"data row239 col4\" >-28215</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col5\" class=\"data row239 col5\" >-1.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row240\" class=\"row_heading level0 row240\" >208</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col0\" class=\"data row240 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col1\" class=\"data row240 col1\" >4</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col2\" class=\"data row240 col2\" >1993239</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col3\" class=\"data row240 col3\" >1961199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col4\" class=\"data row240 col4\" >-32040</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col5\" class=\"data row240 col5\" >-1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row241\" class=\"row_heading level0 row241\" >107</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col0\" class=\"data row241 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col1\" class=\"data row241 col1\" >5</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col2\" class=\"data row241 col2\" >2076573</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col3\" class=\"data row241 col3\" >2044339</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col4\" class=\"data row241 col4\" >-32234</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col5\" class=\"data row241 col5\" >-1.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row242\" class=\"row_heading level0 row242\" >106</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col0\" class=\"data row242 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col1\" class=\"data row242 col1\" >4</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col2\" class=\"data row242 col2\" >2084312</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col3\" class=\"data row242 col3\" >2044517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col4\" class=\"data row242 col4\" >-39795</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col5\" class=\"data row242 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row243\" class=\"row_heading level0 row243\" >117</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col0\" class=\"data row243 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col1\" class=\"data row243 col1\" >15</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col2\" class=\"data row243 col2\" >2170442</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col3\" class=\"data row243 col3\" >2129062</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col4\" class=\"data row243 col4\" >-41380</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col5\" class=\"data row243 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row244\" class=\"row_heading level0 row244\" >112</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col0\" class=\"data row244 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col1\" class=\"data row244 col1\" >10</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col2\" class=\"data row244 col2\" >2142167</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col3\" class=\"data row244 col3\" >2100262</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col4\" class=\"data row244 col4\" >-41905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col5\" class=\"data row244 col5\" >-1.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row245\" class=\"row_heading level0 row245\" >12</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col0\" class=\"data row245 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col1\" class=\"data row245 col1\" >12</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col2\" class=\"data row245 col2\" >4113279</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col3\" class=\"data row245 col3\" >4070682</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col4\" class=\"data row245 col4\" >-42597</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col5\" class=\"data row245 col5\" >-1.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row246\" class=\"row_heading level0 row246\" >284</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col0\" class=\"data row246 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col1\" class=\"data row246 col1\" >80</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col2\" class=\"data row246 col2\" >770509</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col3\" class=\"data row246 col3\" >723310</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col4\" class=\"data row246 col4\" >-47199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col5\" class=\"data row246 col5\" >-6.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row247\" class=\"row_heading level0 row247\" >30</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col0\" class=\"data row247 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col1\" class=\"data row247 col1\" >30</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col2\" class=\"data row247 col2\" >4304239</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col3\" class=\"data row247 col3\" >4255334</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col4\" class=\"data row247 col4\" >-48905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col5\" class=\"data row247 col5\" >-1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row248\" class=\"row_heading level0 row248\" >105</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col0\" class=\"data row248 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col1\" class=\"data row248 col1\" >3</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col2\" class=\"data row248 col2\" >2101272</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col3\" class=\"data row248 col3\" >2049596</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col4\" class=\"data row248 col4\" >-51676</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col5\" class=\"data row248 col5\" >-2.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row249\" class=\"row_heading level0 row249\" >165</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col0\" class=\"data row249 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col1\" class=\"data row249 col1\" >63</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col2\" class=\"data row249 col2\" >1753903</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col3\" class=\"data row249 col3\" >1701014</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col4\" class=\"data row249 col4\" >-52889</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col5\" class=\"data row249 col5\" >-3.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row250\" class=\"row_heading level0 row250\" >207</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col0\" class=\"data row250 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col1\" class=\"data row250 col1\" >3</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col2\" class=\"data row250 col2\" >2010648</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col3\" class=\"data row250 col3\" >1957483</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col4\" class=\"data row250 col4\" >-53165</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col5\" class=\"data row250 col5\" >-2.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row251\" class=\"row_heading level0 row251\" >80</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col0\" class=\"data row251 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col1\" class=\"data row251 col1\" >80</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col2\" class=\"data row251 col2\" >1319725</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col3\" class=\"data row251 col3\" >1262537</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col4\" class=\"data row251 col4\" >-57188</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col5\" class=\"data row251 col5\" >-4.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row252\" class=\"row_heading level0 row252\" >5</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col0\" class=\"data row252 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col1\" class=\"data row252 col1\" >5</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col2\" class=\"data row252 col2\" >4064653</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col3\" class=\"data row252 col3\" >4006900</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col4\" class=\"data row252 col4\" >-57753</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col5\" class=\"data row252 col5\" >-1.42%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row253\" class=\"row_heading level0 row253\" >122</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col0\" class=\"data row253 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col1\" class=\"data row253 col1\" >20</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col2\" class=\"data row253 col2\" >2331845</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col3\" class=\"data row253 col3\" >2271216</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col4\" class=\"data row253 col4\" >-60629</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col5\" class=\"data row253 col5\" >-2.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row254\" class=\"row_heading level0 row254\" >220</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col0\" class=\"data row254 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col1\" class=\"data row254 col1\" >16</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col2\" class=\"data row254 col2\" >2098220</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col3\" class=\"data row254 col3\" >2037134</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col4\" class=\"data row254 col4\" >-61086</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col5\" class=\"data row254 col5\" >-2.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row255\" class=\"row_heading level0 row255\" >104</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col0\" class=\"data row255 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col1\" class=\"data row255 col1\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col2\" class=\"data row255 col2\" >2088685</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col3\" class=\"data row255 col3\" >2023673</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col4\" class=\"data row255 col4\" >-65012</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col5\" class=\"data row255 col5\" >-3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row256\" class=\"row_heading level0 row256\" >206</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col0\" class=\"data row256 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col1\" class=\"data row256 col1\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col2\" class=\"data row256 col2\" >2002177</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col3\" class=\"data row256 col3\" >1935991</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col4\" class=\"data row256 col4\" >-66186</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col5\" class=\"data row256 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row257\" class=\"row_heading level0 row257\" >15</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col0\" class=\"data row257 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col1\" class=\"data row257 col1\" >15</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col2\" class=\"data row257 col2\" >4231002</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col3\" class=\"data row257 col3\" >4164796</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col4\" class=\"data row257 col4\" >-66206</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col5\" class=\"data row257 col5\" >-1.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row258\" class=\"row_heading level0 row258\" >10</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col0\" class=\"data row258 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col1\" class=\"data row258 col1\" >10</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col2\" class=\"data row258 col2\" >4187062</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col3\" class=\"data row258 col3\" >4116942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col4\" class=\"data row258 col4\" >-70120</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col5\" class=\"data row258 col5\" >-1.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row259\" class=\"row_heading level0 row259\" >4</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col0\" class=\"data row259 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col1\" class=\"data row259 col1\" >4</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col2\" class=\"data row259 col2\" >4077551</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col3\" class=\"data row259 col3\" >4005716</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col4\" class=\"data row259 col4\" >-71835</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col5\" class=\"data row259 col5\" >-1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row260\" class=\"row_heading level0 row260\" >254</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col0\" class=\"data row260 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col1\" class=\"data row260 col1\" >50</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col2\" class=\"data row260 col2\" >2355369</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col3\" class=\"data row260 col3\" >2280640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col4\" class=\"data row260 col4\" >-74729</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col5\" class=\"data row260 col5\" >-3.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row261\" class=\"row_heading level0 row261\" >221</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col0\" class=\"data row261 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col1\" class=\"data row261 col1\" >17</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col2\" class=\"data row261 col2\" >2123529</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col3\" class=\"data row261 col3\" >2047152</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col4\" class=\"data row261 col4\" >-76377</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col5\" class=\"data row261 col5\" >-3.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row262\" class=\"row_heading level0 row262\" >152</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col0\" class=\"data row262 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col1\" class=\"data row262 col1\" >50</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col2\" class=\"data row262 col2\" >2290862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col3\" class=\"data row262 col3\" >2211767</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col4\" class=\"data row262 col4\" >-79095</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col5\" class=\"data row262 col5\" >-3.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row263\" class=\"row_heading level0 row263\" >63</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col0\" class=\"data row263 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col1\" class=\"data row263 col1\" >63</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col2\" class=\"data row263 col2\" >3652167</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col3\" class=\"data row263 col3\" >3571610</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col4\" class=\"data row263 col4\" >-80557</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col5\" class=\"data row263 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row264\" class=\"row_heading level0 row264\" >151</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col0\" class=\"data row264 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col1\" class=\"data row264 col1\" >49</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col2\" class=\"data row264 col2\" >2262458</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col3\" class=\"data row264 col3\" >2180214</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col4\" class=\"data row264 col4\" >-82244</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col5\" class=\"data row264 col5\" >-3.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row265\" class=\"row_heading level0 row265\" >118</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col0\" class=\"data row265 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col1\" class=\"data row265 col1\" >16</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col2\" class=\"data row265 col2\" >2215032</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col3\" class=\"data row265 col3\" >2131425</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col4\" class=\"data row265 col4\" >-83607</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col5\" class=\"data row265 col5\" >-3.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row266\" class=\"row_heading level0 row266\" >224</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col0\" class=\"data row266 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col1\" class=\"data row266 col1\" >20</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col2\" class=\"data row266 col2\" >2236672</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col3\" class=\"data row266 col3\" >2150114</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col4\" class=\"data row266 col4\" >-86558</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col5\" class=\"data row266 col5\" >-3.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row267\" class=\"row_heading level0 row267\" >3</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col0\" class=\"data row267 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col1\" class=\"data row267 col1\" >3</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col2\" class=\"data row267 col2\" >4111920</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col3\" class=\"data row267 col3\" >4007079</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col4\" class=\"data row267 col4\" >-104841</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col5\" class=\"data row267 col5\" >-2.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row268\" class=\"row_heading level0 row268\" >140</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col0\" class=\"data row268 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col1\" class=\"data row268 col1\" >38</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col2\" class=\"data row268 col2\" >2028052</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col3\" class=\"data row268 col3\" >1923133</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col4\" class=\"data row268 col4\" >-104919</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col5\" class=\"data row268 col5\" >-5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row269\" class=\"row_heading level0 row269\" >253</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col0\" class=\"data row269 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col1\" class=\"data row269 col1\" >49</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col2\" class=\"data row269 col2\" >2336640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col3\" class=\"data row269 col3\" >2230032</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col4\" class=\"data row269 col4\" >-106608</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col5\" class=\"data row269 col5\" >-4.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row270\" class=\"row_heading level0 row270\" >245</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col0\" class=\"data row270 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col1\" class=\"data row270 col1\" >41</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col2\" class=\"data row270 col2\" >2089576</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col3\" class=\"data row270 col3\" >1978607</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col4\" class=\"data row270 col4\" >-110969</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col5\" class=\"data row270 col5\" >-5.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row271\" class=\"row_heading level0 row271\" >121</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col0\" class=\"data row271 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col1\" class=\"data row271 col1\" >19</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col2\" class=\"data row271 col2\" >2334906</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col3\" class=\"data row271 col3\" >2221910</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col4\" class=\"data row271 col4\" >-112996</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col5\" class=\"data row271 col5\" >-4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row272\" class=\"row_heading level0 row272\" >119</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col0\" class=\"data row272 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col1\" class=\"data row272 col1\" >17</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col2\" class=\"data row272 col2\" >2252838</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col3\" class=\"data row272 col3\" >2139361</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col4\" class=\"data row272 col4\" >-113477</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col5\" class=\"data row272 col5\" >-5.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row273\" class=\"row_heading level0 row273\" >242</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col0\" class=\"data row273 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col1\" class=\"data row273 col1\" >38</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col2\" class=\"data row273 col2\" >2052176</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col3\" class=\"data row273 col3\" >1938503</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col4\" class=\"data row273 col4\" >-113673</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col5\" class=\"data row273 col5\" >-5.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row274\" class=\"row_heading level0 row274\" >222</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col0\" class=\"data row274 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col1\" class=\"data row274 col1\" >18</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col2\" class=\"data row274 col2\" >2185272</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col3\" class=\"data row274 col3\" >2062176</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col4\" class=\"data row274 col4\" >-123096</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col5\" class=\"data row274 col5\" >-5.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row275\" class=\"row_heading level0 row275\" >223</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col0\" class=\"data row275 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col1\" class=\"data row275 col1\" >19</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col2\" class=\"data row275 col2\" >2236505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col3\" class=\"data row275 col3\" >2107128</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col4\" class=\"data row275 col4\" >-129377</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col5\" class=\"data row275 col5\" >-5.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row276\" class=\"row_heading level0 row276\" >2</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col0\" class=\"data row276 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col1\" class=\"data row276 col1\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col2\" class=\"data row276 col2\" >4090862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col3\" class=\"data row276 col3\" >3959664</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col4\" class=\"data row276 col4\" >-131198</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col5\" class=\"data row276 col5\" >-3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row277\" class=\"row_heading level0 row277\" >143</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col0\" class=\"data row277 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col1\" class=\"data row277 col1\" >41</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col2\" class=\"data row277 col2\" >2073902</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col3\" class=\"data row277 col3\" >1941203</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col4\" class=\"data row277 col4\" >-132699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col5\" class=\"data row277 col5\" >-6.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row278\" class=\"row_heading level0 row278\" >147</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col0\" class=\"data row278 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col1\" class=\"data row278 col1\" >45</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col2\" class=\"data row278 col2\" >2201905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col3\" class=\"data row278 col3\" >2067426</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col4\" class=\"data row278 col4\" >-134479</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col5\" class=\"data row278 col5\" >-6.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row279\" class=\"row_heading level0 row279\" >120</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col0\" class=\"data row279 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col1\" class=\"data row279 col1\" >18</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col2\" class=\"data row279 col2\" >2305733</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col3\" class=\"data row279 col3\" >2165744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col4\" class=\"data row279 col4\" >-139989</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col5\" class=\"data row279 col5\" >-6.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row280\" class=\"row_heading level0 row280\" >249</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col0\" class=\"data row280 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col1\" class=\"data row280 col1\" >45</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col2\" class=\"data row280 col2\" >2236654</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col3\" class=\"data row280 col3\" >2095203</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col4\" class=\"data row280 col4\" >-141451</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col5\" class=\"data row280 col5\" >-6.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row281\" class=\"row_heading level0 row281\" >16</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col0\" class=\"data row281 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col1\" class=\"data row281 col1\" >16</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col2\" class=\"data row281 col2\" >4313252</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col3\" class=\"data row281 col3\" >4168559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col4\" class=\"data row281 col4\" >-144693</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col5\" class=\"data row281 col5\" >-3.35%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row282\" class=\"row_heading level0 row282\" >20</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col0\" class=\"data row282 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col1\" class=\"data row282 col1\" >20</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col2\" class=\"data row282 col2\" >4568517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col3\" class=\"data row282 col3\" >4421330</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col4\" class=\"data row282 col4\" >-147187</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col5\" class=\"data row282 col5\" >-3.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row283\" class=\"row_heading level0 row283\" >50</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col0\" class=\"data row283 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col1\" class=\"data row283 col1\" >50</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col2\" class=\"data row283 col2\" >4646231</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col3\" class=\"data row283 col3\" >4492407</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col4\" class=\"data row283 col4\" >-153824</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col5\" class=\"data row283 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row284\" class=\"row_heading level0 row284\" >141</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col0\" class=\"data row284 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col1\" class=\"data row284 col1\" >39</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col2\" class=\"data row284 col2\" >2148718</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col3\" class=\"data row284 col3\" >1986712</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col4\" class=\"data row284 col4\" >-162006</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col5\" class=\"data row284 col5\" >-7.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row285\" class=\"row_heading level0 row285\" >150</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col0\" class=\"data row285 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col1\" class=\"data row285 col1\" >48</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col2\" class=\"data row285 col2\" >2235296</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col3\" class=\"data row285 col3\" >2058392</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col4\" class=\"data row285 col4\" >-176904</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col5\" class=\"data row285 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row286\" class=\"row_heading level0 row286\" >243</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col0\" class=\"data row286 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col1\" class=\"data row286 col1\" >39</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col2\" class=\"data row286 col2\" >2175745</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col3\" class=\"data row286 col3\" >1995795</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col4\" class=\"data row286 col4\" >-179950</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col5\" class=\"data row286 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row287\" class=\"row_heading level0 row287\" >49</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col0\" class=\"data row287 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col1\" class=\"data row287 col1\" >49</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col2\" class=\"data row287 col2\" >4599098</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col3\" class=\"data row287 col3\" >4410246</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col4\" class=\"data row287 col4\" >-188852</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col5\" class=\"data row287 col5\" >-4.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row288\" class=\"row_heading level0 row288\" >17</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col0\" class=\"data row288 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col1\" class=\"data row288 col1\" >17</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col2\" class=\"data row288 col2\" >4376367</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col3\" class=\"data row288 col3\" >4186513</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col4\" class=\"data row288 col4\" >-189854</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col5\" class=\"data row288 col5\" >-4.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row289\" class=\"row_heading level0 row289\" >252</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col0\" class=\"data row289 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col1\" class=\"data row289 col1\" >48</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col2\" class=\"data row289 col2\" >2299367</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col3\" class=\"data row289 col3\" >2101346</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col4\" class=\"data row289 col4\" >-198021</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col5\" class=\"data row289 col5\" >-8.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row290\" class=\"row_heading level0 row290\" >148</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col0\" class=\"data row290 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col1\" class=\"data row290 col1\" >46</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col2\" class=\"data row290 col2\" >2238774</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col3\" class=\"data row290 col3\" >2023033</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col4\" class=\"data row290 col4\" >-215741</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col5\" class=\"data row290 col5\" >-9.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row291\" class=\"row_heading level0 row291\" >149</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col0\" class=\"data row291 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col1\" class=\"data row291 col1\" >47</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col2\" class=\"data row291 col2\" >2237940</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col3\" class=\"data row291 col3\" >2019517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col4\" class=\"data row291 col4\" >-218423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col5\" class=\"data row291 col5\" >-9.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row292\" class=\"row_heading level0 row292\" >38</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col0\" class=\"data row292 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col1\" class=\"data row292 col1\" >38</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col2\" class=\"data row292 col2\" >4080228</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col3\" class=\"data row292 col3\" >3861636</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col4\" class=\"data row292 col4\" >-218592</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col5\" class=\"data row292 col5\" >-5.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row293\" class=\"row_heading level0 row293\" >251</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col0\" class=\"data row293 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col1\" class=\"data row293 col1\" >47</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col2\" class=\"data row293 col2\" >2297533</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col3\" class=\"data row293 col3\" >2063366</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col4\" class=\"data row293 col4\" >-234167</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col5\" class=\"data row293 col5\" >-10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row294\" class=\"row_heading level0 row294\" >250</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col0\" class=\"data row294 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col1\" class=\"data row294 col1\" >46</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col2\" class=\"data row294 col2\" >2290942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col3\" class=\"data row294 col3\" >2054118</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col4\" class=\"data row294 col4\" >-236824</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col5\" class=\"data row294 col5\" >-10.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row295\" class=\"row_heading level0 row295\" >19</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col0\" class=\"data row295 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col1\" class=\"data row295 col1\" >19</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col2\" class=\"data row295 col2\" >4571411</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col3\" class=\"data row295 col3\" >4329038</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col4\" class=\"data row295 col4\" >-242373</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col5\" class=\"data row295 col5\" >-5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row296\" class=\"row_heading level0 row296\" >41</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col0\" class=\"data row296 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col1\" class=\"data row296 col1\" >41</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col2\" class=\"data row296 col2\" >4163478</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col3\" class=\"data row296 col3\" >3919810</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col4\" class=\"data row296 col4\" >-243668</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col5\" class=\"data row296 col5\" >-5.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row297\" class=\"row_heading level0 row297\" >244</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col0\" class=\"data row297 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col1\" class=\"data row297 col1\" >40</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col2\" class=\"data row297 col2\" >2197964</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col3\" class=\"data row297 col3\" >1942194</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col4\" class=\"data row297 col4\" >-255770</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col5\" class=\"data row297 col5\" >-11.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row298\" class=\"row_heading level0 row298\" >18</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col0\" class=\"data row298 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col1\" class=\"data row298 col1\" >18</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col2\" class=\"data row298 col2\" >4491005</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col3\" class=\"data row298 col3\" >4227920</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col4\" class=\"data row298 col4\" >-263085</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col5\" class=\"data row298 col5\" >-5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row299\" class=\"row_heading level0 row299\" >142</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col0\" class=\"data row299 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col1\" class=\"data row299 col1\" >40</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col2\" class=\"data row299 col2\" >2189516</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col3\" class=\"data row299 col3\" >1917201</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col4\" class=\"data row299 col4\" >-272315</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col5\" class=\"data row299 col5\" >-12.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row300\" class=\"row_heading level0 row300\" >45</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col0\" class=\"data row300 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col1\" class=\"data row300 col1\" >45</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col2\" class=\"data row300 col2\" >4438559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col3\" class=\"data row300 col3\" >4162629</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col4\" class=\"data row300 col4\" >-275930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col5\" class=\"data row300 col5\" >-6.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row301\" class=\"row_heading level0 row301\" >39</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col0\" class=\"data row301 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col1\" class=\"data row301 col1\" >39</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col2\" class=\"data row301 col2\" >4324463</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col3\" class=\"data row301 col3\" >3982507</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col4\" class=\"data row301 col4\" >-341956</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col5\" class=\"data row301 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row302\" class=\"row_heading level0 row302\" >48</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col0\" class=\"data row302 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col1\" class=\"data row302 col1\" >48</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col2\" class=\"data row302 col2\" >4534663</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col3\" class=\"data row302 col3\" >4159738</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col4\" class=\"data row302 col4\" >-374925</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col5\" class=\"data row302 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row303\" class=\"row_heading level0 row303\" >46</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col0\" class=\"data row303 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col1\" class=\"data row303 col1\" >46</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col2\" class=\"data row303 col2\" >4529716</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col3\" class=\"data row303 col3\" >4077151</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col4\" class=\"data row303 col4\" >-452565</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col5\" class=\"data row303 col5\" >-9.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row304\" class=\"row_heading level0 row304\" >47</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col0\" class=\"data row304 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col1\" class=\"data row304 col1\" >47</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col2\" class=\"data row304 col2\" >4535473</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col3\" class=\"data row304 col3\" >4082883</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col4\" class=\"data row304 col4\" >-452590</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col5\" class=\"data row304 col5\" >-9.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row305\" class=\"row_heading level0 row305\" >40</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col0\" class=\"data row305 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col1\" class=\"data row305 col1\" >40</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col2\" class=\"data row305 col2\" >4387480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col3\" class=\"data row305 col3\" >3859395</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col4\" class=\"data row305 col4\" >-528085</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col5\" class=\"data row305 col5\" >-12.04%</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd9c3fc23d0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "census.sort_values('Change', ascending=False).style.format({'Percent Change': \"{:,.2%}\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Not surprisingly, the top row of the sorted table is the line that corresponds to the entire population: both sexes and all age groups. From 2010 to 2014, the population of the United States increased by about 9.5 million people, a change of just over 3%.\n",
+    "\n",
+    "The next two rows correspond to all the men and all the women respectively. The male population grew more than the female population, both in absolute and percentage terms. Both percent changes were around 3%.\n",
+    "\n",
+    "Now take a look at the next few rows. The percent change jumps from about 3% for the overall population to almost 30% for the people in their late sixties and early seventies. This stunning change contributes to what is known as the greying of America.\n",
+    "\n",
+    "By far the greatest absolute change was among those in the 64-67 agegroup in 2014. What could explain this large increase? We can explore this question by examining the years in which the relevant groups were born.\n",
+    "\n",
+    "- Those who were in the 64-67 age group in 2010 were born in the years 1943 to 1946. The attack on Pearl Harbor was in late 1941, and by 1942 U.S. forces were heavily engaged in a massive war that ended in 1945. \n",
+    "\n",
+    "- Those who were 64 to 67 years old in 2014 were born in the years 1947 to 1950, at the height of the post-WWII baby boom in the United States. \n",
+    "\n",
+    "The post-war jump in births is the major reason for the large changes that we have observed."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/3/Example_Trends_in_the_Population_of_the_United_States.ipynb

@@ -0,0 +1,6239 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Example: Population Trends\n",
+    "\n",
+    "We are now ready to work with large tables of data. The file below contains \"Annual Estimates of the Resident Population by Single Year of Age and Sex for the United States.\" Notice that `read_table` can read data directly from a URL."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>CENSUS2010POP</th>\n",
+       "      <th>ESTIMATESBASE2010</th>\n",
+       "      <th>POPESTIMATE2010</th>\n",
+       "      <th>POPESTIMATE2011</th>\n",
+       "      <th>POPESTIMATE2012</th>\n",
+       "      <th>POPESTIMATE2013</th>\n",
+       "      <th>POPESTIMATE2014</th>\n",
+       "      <th>POPESTIMATE2015</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3944153</td>\n",
+       "      <td>3944160</td>\n",
+       "      <td>3951330</td>\n",
+       "      <td>3963087</td>\n",
+       "      <td>3926540</td>\n",
+       "      <td>3931141</td>\n",
+       "      <td>3949775</td>\n",
+       "      <td>3978038</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3978070</td>\n",
+       "      <td>3978090</td>\n",
+       "      <td>3957888</td>\n",
+       "      <td>3966551</td>\n",
+       "      <td>3977939</td>\n",
+       "      <td>3942872</td>\n",
+       "      <td>3949776</td>\n",
+       "      <td>3968564</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4096929</td>\n",
+       "      <td>4096939</td>\n",
+       "      <td>4090862</td>\n",
+       "      <td>3971565</td>\n",
+       "      <td>3980095</td>\n",
+       "      <td>3992720</td>\n",
+       "      <td>3959664</td>\n",
+       "      <td>3966583</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4119040</td>\n",
+       "      <td>4119051</td>\n",
+       "      <td>4111920</td>\n",
+       "      <td>4102470</td>\n",
+       "      <td>3983157</td>\n",
+       "      <td>3992734</td>\n",
+       "      <td>4007079</td>\n",
+       "      <td>3974061</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4063170</td>\n",
+       "      <td>4063186</td>\n",
+       "      <td>4077551</td>\n",
+       "      <td>4122294</td>\n",
+       "      <td>4112849</td>\n",
+       "      <td>3994449</td>\n",
+       "      <td>4005716</td>\n",
+       "      <td>4020035</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>301</th>\n",
+       "      <td>2</td>\n",
+       "      <td>97</td>\n",
+       "      <td>53582</td>\n",
+       "      <td>53605</td>\n",
+       "      <td>54118</td>\n",
+       "      <td>57159</td>\n",
+       "      <td>59533</td>\n",
+       "      <td>61255</td>\n",
+       "      <td>62779</td>\n",
+       "      <td>69285</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>302</th>\n",
+       "      <td>2</td>\n",
+       "      <td>98</td>\n",
+       "      <td>36641</td>\n",
+       "      <td>36675</td>\n",
+       "      <td>37532</td>\n",
+       "      <td>40116</td>\n",
+       "      <td>42857</td>\n",
+       "      <td>44359</td>\n",
+       "      <td>46208</td>\n",
+       "      <td>47272</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>2</td>\n",
+       "      <td>99</td>\n",
+       "      <td>26193</td>\n",
+       "      <td>26214</td>\n",
+       "      <td>26074</td>\n",
+       "      <td>27030</td>\n",
+       "      <td>29320</td>\n",
+       "      <td>31112</td>\n",
+       "      <td>32517</td>\n",
+       "      <td>34064</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>304</th>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>44202</td>\n",
+       "      <td>44246</td>\n",
+       "      <td>45058</td>\n",
+       "      <td>47556</td>\n",
+       "      <td>50661</td>\n",
+       "      <td>53902</td>\n",
+       "      <td>58008</td>\n",
+       "      <td>61886</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>305</th>\n",
+       "      <td>2</td>\n",
+       "      <td>999</td>\n",
+       "      <td>156964212</td>\n",
+       "      <td>156969328</td>\n",
+       "      <td>157258820</td>\n",
+       "      <td>158427085</td>\n",
+       "      <td>159581546</td>\n",
+       "      <td>160720625</td>\n",
+       "      <td>161952064</td>\n",
+       "      <td>163189523</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>306 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     SEX  AGE  CENSUS2010POP  ESTIMATESBASE2010  POPESTIMATE2010  \\\n",
+       "0      0    0        3944153            3944160          3951330   \n",
+       "1      0    1        3978070            3978090          3957888   \n",
+       "2      0    2        4096929            4096939          4090862   \n",
+       "3      0    3        4119040            4119051          4111920   \n",
+       "4      0    4        4063170            4063186          4077551   \n",
+       "..   ...  ...            ...                ...              ...   \n",
+       "301    2   97          53582              53605            54118   \n",
+       "302    2   98          36641              36675            37532   \n",
+       "303    2   99          26193              26214            26074   \n",
+       "304    2  100          44202              44246            45058   \n",
+       "305    2  999      156964212          156969328        157258820   \n",
+       "\n",
+       "     POPESTIMATE2011  POPESTIMATE2012  POPESTIMATE2013  POPESTIMATE2014  \\\n",
+       "0            3963087          3926540          3931141          3949775   \n",
+       "1            3966551          3977939          3942872          3949776   \n",
+       "2            3971565          3980095          3992720          3959664   \n",
+       "3            4102470          3983157          3992734          4007079   \n",
+       "4            4122294          4112849          3994449          4005716   \n",
+       "..               ...              ...              ...              ...   \n",
+       "301            57159            59533            61255            62779   \n",
+       "302            40116            42857            44359            46208   \n",
+       "303            27030            29320            31112            32517   \n",
+       "304            47556            50661            53902            58008   \n",
+       "305        158427085        159581546        160720625        161952064   \n",
+       "\n",
+       "     POPESTIMATE2015  \n",
+       "0            3978038  \n",
+       "1            3968564  \n",
+       "2            3966583  \n",
+       "3            3974061  \n",
+       "4            4020035  \n",
+       "..               ...  \n",
+       "301            69285  \n",
+       "302            47272  \n",
+       "303            34064  \n",
+       "304            61886  \n",
+       "305        163189523  \n",
+       "\n",
+       "[306 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# As of Jan 2017, this census file is online here: \n",
+    "data = 'http://www2.census.gov/programs-surveys/popest/datasets/2010-2015/national/asrh/nc-est2015-agesex-res.csv'\n",
+    "\n",
+    "# A local copy can be accessed here in case census.gov moves the file:\n",
+    "# data = path_data + 'nc-est2015-agesex-res.csv'\n",
+    "\n",
+    "full_census_table = pd.read_csv(data)\n",
+    "full_census_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Only the first 5 and last 5 rows of the DataFrame are displayed. Later we will see how to display the entire DataFrame; however, this is typically not useful with large tables.\n",
+    "\n",
+    "a [description of the table](http://www2.census.gov/programs-surveys/popest/datasets/2010-2015/national/asrh/nc-est2015-agesex-res.pdf) appears online. The `SEX` column contains numeric codes: `0` stands for the total, `1` for male, and `2` for female. The `AGE` column contains ages in completed years, but the special value `999` is a sum of the total population. The rest of the columns contain estimates of the US population.\n",
+    "\n",
+    "Typically, a public table will contain more information than necessary for a particular investigation or analysis. In this case, let us suppose that we are only interested in the population changes from 2010 to 2014. Let us `select` the relevant columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>POPESTIMATE2010</th>\n",
+       "      <th>POPESTIMATE2014</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3951330</td>\n",
+       "      <td>3949775</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3957888</td>\n",
+       "      <td>3949776</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4090862</td>\n",
+       "      <td>3959664</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4111920</td>\n",
+       "      <td>4007079</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4077551</td>\n",
+       "      <td>4005716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>301</th>\n",
+       "      <td>2</td>\n",
+       "      <td>97</td>\n",
+       "      <td>54118</td>\n",
+       "      <td>62779</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>302</th>\n",
+       "      <td>2</td>\n",
+       "      <td>98</td>\n",
+       "      <td>37532</td>\n",
+       "      <td>46208</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>2</td>\n",
+       "      <td>99</td>\n",
+       "      <td>26074</td>\n",
+       "      <td>32517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>304</th>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>45058</td>\n",
+       "      <td>58008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>305</th>\n",
+       "      <td>2</td>\n",
+       "      <td>999</td>\n",
+       "      <td>157258820</td>\n",
+       "      <td>161952064</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>306 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     SEX  AGE  POPESTIMATE2010  POPESTIMATE2014\n",
+       "0      0    0          3951330          3949775\n",
+       "1      0    1          3957888          3949776\n",
+       "2      0    2          4090862          3959664\n",
+       "3      0    3          4111920          4007079\n",
+       "4      0    4          4077551          4005716\n",
+       "..   ...  ...              ...              ...\n",
+       "301    2   97            54118            62779\n",
+       "302    2   98            37532            46208\n",
+       "303    2   99            26074            32517\n",
+       "304    2  100            45058            58008\n",
+       "305    2  999        157258820        161952064\n",
+       "\n",
+       "[306 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "partial_census_table = full_census_table[['SEX', 'AGE', 'POPESTIMATE2010', 'POPESTIMATE2014']]\n",
+    "partial_census_table"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can also simplify the labels of the selected columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SEX</th>\n",
+       "      <th>AGE</th>\n",
+       "      <th>2010</th>\n",
+       "      <th>2014</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3951330</td>\n",
+       "      <td>3949775</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3957888</td>\n",
+       "      <td>3949776</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>4090862</td>\n",
+       "      <td>3959664</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>4111920</td>\n",
+       "      <td>4007079</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4077551</td>\n",
+       "      <td>4005716</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>301</th>\n",
+       "      <td>2</td>\n",
+       "      <td>97</td>\n",
+       "      <td>54118</td>\n",
+       "      <td>62779</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>302</th>\n",
+       "      <td>2</td>\n",
+       "      <td>98</td>\n",
+       "      <td>37532</td>\n",
+       "      <td>46208</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>303</th>\n",
+       "      <td>2</td>\n",
+       "      <td>99</td>\n",
+       "      <td>26074</td>\n",
+       "      <td>32517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>304</th>\n",
+       "      <td>2</td>\n",
+       "      <td>100</td>\n",
+       "      <td>45058</td>\n",
+       "      <td>58008</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>305</th>\n",
+       "      <td>2</td>\n",
+       "      <td>999</td>\n",
+       "      <td>157258820</td>\n",
+       "      <td>161952064</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>306 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     SEX  AGE       2010       2014\n",
+       "0      0    0    3951330    3949775\n",
+       "1      0    1    3957888    3949776\n",
+       "2      0    2    4090862    3959664\n",
+       "3      0    3    4111920    4007079\n",
+       "4      0    4    4077551    4005716\n",
+       "..   ...  ...        ...        ...\n",
+       "301    2   97      54118      62779\n",
+       "302    2   98      37532      46208\n",
+       "303    2   99      26074      32517\n",
+       "304    2  100      45058      58008\n",
+       "305    2  999  157258820  161952064\n",
+       "\n",
+       "[306 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "us_pop = partial_census_table.rename(columns={'POPESTIMATE2010': '2010', 'POPESTIMATE2014':'2014'})\n",
+    "us_pop"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now have a table that is easy to work with. Each column of the table is an array of the same length, and so columns can be combined using arithmetic. Here is the change in population between 2010 and 2014."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        -1555\n",
+       "1        -8112\n",
+       "2      -131198\n",
+       "3      -104841\n",
+       "4       -71835\n",
+       "        ...   \n",
+       "301       8661\n",
+       "302       8676\n",
+       "303       6443\n",
+       "304      12950\n",
+       "305    4693244\n",
+       "Length: 306, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "us_pop['2014'] - us_pop['2010']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let us augment `us_pop` with a column that contains these changes, both in absolute terms and as percents relative to the value in 2010."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >SEX</th>        <th class=\"col_heading level0 col1\" >AGE</th>        <th class=\"col_heading level0 col2\" >2010</th>        <th class=\"col_heading level0 col3\" >2014</th>        <th class=\"col_heading level0 col4\" >Change</th>        <th class=\"col_heading level0 col5\" >Percent Change</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col0\" class=\"data row0 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col1\" class=\"data row0 col1\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col2\" class=\"data row0 col2\" >3951330</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col3\" class=\"data row0 col3\" >3949775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col4\" class=\"data row0 col4\" >-1555</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row0_col5\" class=\"data row0 col5\" >-0.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col0\" class=\"data row1 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col1\" class=\"data row1 col1\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col2\" class=\"data row1 col2\" >3957888</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col3\" class=\"data row1 col3\" >3949776</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col4\" class=\"data row1 col4\" >-8112</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row1_col5\" class=\"data row1 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col0\" class=\"data row2 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col1\" class=\"data row2 col1\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col2\" class=\"data row2 col2\" >4090862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col3\" class=\"data row2 col3\" >3959664</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col4\" class=\"data row2 col4\" >-131198</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row2_col5\" class=\"data row2 col5\" >-3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col0\" class=\"data row3 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col1\" class=\"data row3 col1\" >3</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col2\" class=\"data row3 col2\" >4111920</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col3\" class=\"data row3 col3\" >4007079</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col4\" class=\"data row3 col4\" >-104841</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row3_col5\" class=\"data row3 col5\" >-2.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col0\" class=\"data row4 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col1\" class=\"data row4 col1\" >4</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col2\" class=\"data row4 col2\" >4077551</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col3\" class=\"data row4 col3\" >4005716</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col4\" class=\"data row4 col4\" >-71835</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row4_col5\" class=\"data row4 col5\" >-1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col0\" class=\"data row5 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col1\" class=\"data row5 col1\" >5</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col2\" class=\"data row5 col2\" >4064653</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col3\" class=\"data row5 col3\" >4006900</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col4\" class=\"data row5 col4\" >-57753</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row5_col5\" class=\"data row5 col5\" >-1.42%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col0\" class=\"data row6 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col1\" class=\"data row6 col1\" >6</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col2\" class=\"data row6 col2\" >4073013</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col3\" class=\"data row6 col3\" >4135930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col4\" class=\"data row6 col4\" >62917</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row6_col5\" class=\"data row6 col5\" >1.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col0\" class=\"data row7 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col1\" class=\"data row7 col1\" >7</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col2\" class=\"data row7 col2\" >4043046</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col3\" class=\"data row7 col3\" >4155326</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col4\" class=\"data row7 col4\" >112280</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row7_col5\" class=\"data row7 col5\" >2.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col0\" class=\"data row8 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col1\" class=\"data row8 col1\" >8</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col2\" class=\"data row8 col2\" >4025604</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col3\" class=\"data row8 col3\" >4120903</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col4\" class=\"data row8 col4\" >95299</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row8_col5\" class=\"data row8 col5\" >2.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col0\" class=\"data row9 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col1\" class=\"data row9 col1\" >9</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col2\" class=\"data row9 col2\" >4125415</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col3\" class=\"data row9 col3\" >4108349</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col4\" class=\"data row9 col4\" >-17066</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row9_col5\" class=\"data row9 col5\" >-0.41%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col0\" class=\"data row10 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col1\" class=\"data row10 col1\" >10</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col2\" class=\"data row10 col2\" >4187062</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col3\" class=\"data row10 col3\" >4116942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col4\" class=\"data row10 col4\" >-70120</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row10_col5\" class=\"data row10 col5\" >-1.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col0\" class=\"data row11 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col1\" class=\"data row11 col1\" >11</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col2\" class=\"data row11 col2\" >4115511</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col3\" class=\"data row11 col3\" >4087402</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col4\" class=\"data row11 col4\" >-28109</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row11_col5\" class=\"data row11 col5\" >-0.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col0\" class=\"data row12 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col1\" class=\"data row12 col1\" >12</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col2\" class=\"data row12 col2\" >4113279</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col3\" class=\"data row12 col3\" >4070682</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col4\" class=\"data row12 col4\" >-42597</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row12_col5\" class=\"data row12 col5\" >-1.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col0\" class=\"data row13 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col1\" class=\"data row13 col1\" >13</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col2\" class=\"data row13 col2\" >4119666</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col3\" class=\"data row13 col3\" >4171030</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col4\" class=\"data row13 col4\" >51364</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row13_col5\" class=\"data row13 col5\" >1.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col0\" class=\"data row14 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col1\" class=\"data row14 col1\" >14</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col2\" class=\"data row14 col2\" >4145614</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col3\" class=\"data row14 col3\" >4233839</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col4\" class=\"data row14 col4\" >88225</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row14_col5\" class=\"data row14 col5\" >2.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col0\" class=\"data row15 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col1\" class=\"data row15 col1\" >15</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col2\" class=\"data row15 col2\" >4231002</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col3\" class=\"data row15 col3\" >4164796</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col4\" class=\"data row15 col4\" >-66206</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row15_col5\" class=\"data row15 col5\" >-1.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col0\" class=\"data row16 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col1\" class=\"data row16 col1\" >16</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col2\" class=\"data row16 col2\" >4313252</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col3\" class=\"data row16 col3\" >4168559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col4\" class=\"data row16 col4\" >-144693</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row16_col5\" class=\"data row16 col5\" >-3.35%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col0\" class=\"data row17 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col1\" class=\"data row17 col1\" >17</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col2\" class=\"data row17 col2\" >4376367</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col3\" class=\"data row17 col3\" >4186513</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col4\" class=\"data row17 col4\" >-189854</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row17_col5\" class=\"data row17 col5\" >-4.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col0\" class=\"data row18 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col1\" class=\"data row18 col1\" >18</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col2\" class=\"data row18 col2\" >4491005</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col3\" class=\"data row18 col3\" >4227920</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col4\" class=\"data row18 col4\" >-263085</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row18_col5\" class=\"data row18 col5\" >-5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col0\" class=\"data row19 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col1\" class=\"data row19 col1\" >19</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col2\" class=\"data row19 col2\" >4571411</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col3\" class=\"data row19 col3\" >4329038</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col4\" class=\"data row19 col4\" >-242373</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row19_col5\" class=\"data row19 col5\" >-5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col0\" class=\"data row20 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col1\" class=\"data row20 col1\" >20</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col2\" class=\"data row20 col2\" >4568517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col3\" class=\"data row20 col3\" >4421330</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col4\" class=\"data row20 col4\" >-147187</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row20_col5\" class=\"data row20 col5\" >-3.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col0\" class=\"data row21 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col1\" class=\"data row21 col1\" >21</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col2\" class=\"data row21 col2\" >4387956</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col3\" class=\"data row21 col3\" >4492373</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col4\" class=\"data row21 col4\" >104417</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row21_col5\" class=\"data row21 col5\" >2.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col0\" class=\"data row22 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col1\" class=\"data row22 col1\" >22</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col2\" class=\"data row22 col2\" >4287005</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col3\" class=\"data row22 col3\" >4615729</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col4\" class=\"data row22 col4\" >328724</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row22_col5\" class=\"data row22 col5\" >7.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col0\" class=\"data row23 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col1\" class=\"data row23 col1\" >23</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col2\" class=\"data row23 col2\" >4217228</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col3\" class=\"data row23 col3\" >4702156</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col4\" class=\"data row23 col4\" >484928</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row23_col5\" class=\"data row23 col5\" >11.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col0\" class=\"data row24 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col1\" class=\"data row24 col1\" >24</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col2\" class=\"data row24 col2\" >4243602</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col3\" class=\"data row24 col3\" >4695411</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col4\" class=\"data row24 col4\" >451809</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row24_col5\" class=\"data row24 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col0\" class=\"data row25 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col1\" class=\"data row25 col1\" >25</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col2\" class=\"data row25 col2\" >4289428</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col3\" class=\"data row25 col3\" >4511370</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col4\" class=\"data row25 col4\" >221942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row25_col5\" class=\"data row25 col5\" >5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col0\" class=\"data row26 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col1\" class=\"data row26 col1\" >26</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col2\" class=\"data row26 col2\" >4160806</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col3\" class=\"data row26 col3\" >4408043</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col4\" class=\"data row26 col4\" >247237</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row26_col5\" class=\"data row26 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col0\" class=\"data row27 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col1\" class=\"data row27 col1\" >27</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col2\" class=\"data row27 col2\" >4237026</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col3\" class=\"data row27 col3\" >4334806</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col4\" class=\"data row27 col4\" >97780</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row27_col5\" class=\"data row27 col5\" >2.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col0\" class=\"data row28 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col1\" class=\"data row28 col1\" >28</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col2\" class=\"data row28 col2\" >4247541</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col3\" class=\"data row28 col3\" >4355240</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col4\" class=\"data row28 col4\" >107699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row28_col5\" class=\"data row28 col5\" >2.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col0\" class=\"data row29 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col1\" class=\"data row29 col1\" >29</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col2\" class=\"data row29 col2\" >4210286</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col3\" class=\"data row29 col3\" >4391788</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col4\" class=\"data row29 col4\" >181502</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row29_col5\" class=\"data row29 col5\" >4.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col0\" class=\"data row30 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col1\" class=\"data row30 col1\" >30</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col2\" class=\"data row30 col2\" >4304239</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col3\" class=\"data row30 col3\" >4255334</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col4\" class=\"data row30 col4\" >-48905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row30_col5\" class=\"data row30 col5\" >-1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col0\" class=\"data row31 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col1\" class=\"data row31 col1\" >31</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col2\" class=\"data row31 col2\" >4042516</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col3\" class=\"data row31 col3\" >4323217</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col4\" class=\"data row31 col4\" >280701</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row31_col5\" class=\"data row31 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col0\" class=\"data row32 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col1\" class=\"data row32 col1\" >32</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col2\" class=\"data row32 col2\" >3967602</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col3\" class=\"data row32 col3\" >4323951</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col4\" class=\"data row32 col4\" >356349</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row32_col5\" class=\"data row32 col5\" >8.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col0\" class=\"data row33 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col1\" class=\"data row33 col1\" >33</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col2\" class=\"data row33 col2\" >3933581</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col3\" class=\"data row33 col3\" >4278664</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col4\" class=\"data row33 col4\" >345083</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row33_col5\" class=\"data row33 col5\" >8.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col0\" class=\"data row34 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col1\" class=\"data row34 col1\" >34</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col2\" class=\"data row34 col2\" >3822189</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col3\" class=\"data row34 col3\" >4364748</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col4\" class=\"data row34 col4\" >542559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row34_col5\" class=\"data row34 col5\" >14.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col0\" class=\"data row35 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col1\" class=\"data row35 col1\" >35</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col2\" class=\"data row35 col2\" >3948335</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col3\" class=\"data row35 col3\" >4095782</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col4\" class=\"data row35 col4\" >147447</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row35_col5\" class=\"data row35 col5\" >3.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col0\" class=\"data row36 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col1\" class=\"data row36 col1\" >36</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col2\" class=\"data row36 col2\" >3830199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col3\" class=\"data row36 col3\" >4016711</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col4\" class=\"data row36 col4\" >186512</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row36_col5\" class=\"data row36 col5\" >4.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col0\" class=\"data row37 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col1\" class=\"data row37 col1\" >37</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col2\" class=\"data row37 col2\" >3896766</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col3\" class=\"data row37 col3\" >3976750</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col4\" class=\"data row37 col4\" >79984</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row37_col5\" class=\"data row37 col5\" >2.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col0\" class=\"data row38 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col1\" class=\"data row38 col1\" >38</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col2\" class=\"data row38 col2\" >4080228</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col3\" class=\"data row38 col3\" >3861636</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col4\" class=\"data row38 col4\" >-218592</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row38_col5\" class=\"data row38 col5\" >-5.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col0\" class=\"data row39 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col1\" class=\"data row39 col1\" >39</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col2\" class=\"data row39 col2\" >4324463</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col3\" class=\"data row39 col3\" >3982507</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col4\" class=\"data row39 col4\" >-341956</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row39_col5\" class=\"data row39 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col0\" class=\"data row40 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col1\" class=\"data row40 col1\" >40</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col2\" class=\"data row40 col2\" >4387480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col3\" class=\"data row40 col3\" >3859395</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col4\" class=\"data row40 col4\" >-528085</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row40_col5\" class=\"data row40 col5\" >-12.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col0\" class=\"data row41 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col1\" class=\"data row41 col1\" >41</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col2\" class=\"data row41 col2\" >4163478</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col3\" class=\"data row41 col3\" >3919810</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col4\" class=\"data row41 col4\" >-243668</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row41_col5\" class=\"data row41 col5\" >-5.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col0\" class=\"data row42 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col1\" class=\"data row42 col1\" >42</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col2\" class=\"data row42 col2\" >4082712</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col3\" class=\"data row42 col3\" >4097698</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col4\" class=\"data row42 col4\" >14986</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row42_col5\" class=\"data row42 col5\" >0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col0\" class=\"data row43 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col1\" class=\"data row43 col1\" >43</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col2\" class=\"data row43 col2\" >4093844</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col3\" class=\"data row43 col3\" >4333850</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col4\" class=\"data row43 col4\" >240006</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row43_col5\" class=\"data row43 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col0\" class=\"data row44 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col1\" class=\"data row44 col1\" >44</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col2\" class=\"data row44 col2\" >4178508</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col3\" class=\"data row44 col3\" >4390283</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col4\" class=\"data row44 col4\" >211775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row44_col5\" class=\"data row44 col5\" >5.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col0\" class=\"data row45 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col1\" class=\"data row45 col1\" >45</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col2\" class=\"data row45 col2\" >4438559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col3\" class=\"data row45 col3\" >4162629</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col4\" class=\"data row45 col4\" >-275930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row45_col5\" class=\"data row45 col5\" >-6.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col0\" class=\"data row46 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col1\" class=\"data row46 col1\" >46</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col2\" class=\"data row46 col2\" >4529716</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col3\" class=\"data row46 col3\" >4077151</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col4\" class=\"data row46 col4\" >-452565</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row46_col5\" class=\"data row46 col5\" >-9.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col0\" class=\"data row47 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col1\" class=\"data row47 col1\" >47</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col2\" class=\"data row47 col2\" >4535473</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col3\" class=\"data row47 col3\" >4082883</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col4\" class=\"data row47 col4\" >-452590</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row47_col5\" class=\"data row47 col5\" >-9.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row48\" class=\"row_heading level0 row48\" >48</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col0\" class=\"data row48 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col1\" class=\"data row48 col1\" >48</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col2\" class=\"data row48 col2\" >4534663</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col3\" class=\"data row48 col3\" >4159738</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col4\" class=\"data row48 col4\" >-374925</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row48_col5\" class=\"data row48 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row49\" class=\"row_heading level0 row49\" >49</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col0\" class=\"data row49 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col1\" class=\"data row49 col1\" >49</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col2\" class=\"data row49 col2\" >4599098</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col3\" class=\"data row49 col3\" >4410246</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col4\" class=\"data row49 col4\" >-188852</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row49_col5\" class=\"data row49 col5\" >-4.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row50\" class=\"row_heading level0 row50\" >50</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col0\" class=\"data row50 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col1\" class=\"data row50 col1\" >50</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col2\" class=\"data row50 col2\" >4646231</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col3\" class=\"data row50 col3\" >4492407</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col4\" class=\"data row50 col4\" >-153824</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row50_col5\" class=\"data row50 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row51\" class=\"row_heading level0 row51\" >51</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col0\" class=\"data row51 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col1\" class=\"data row51 col1\" >51</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col2\" class=\"data row51 col2\" >4498974</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col3\" class=\"data row51 col3\" >4489393</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col4\" class=\"data row51 col4\" >-9581</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row51_col5\" class=\"data row51 col5\" >-0.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row52\" class=\"row_heading level0 row52\" >52</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col0\" class=\"data row52 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col1\" class=\"data row52 col1\" >52</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col2\" class=\"data row52 col2\" >4480584</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col3\" class=\"data row52 col3\" >4480188</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col4\" class=\"data row52 col4\" >-396</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row52_col5\" class=\"data row52 col5\" >-0.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row53\" class=\"row_heading level0 row53\" >53</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col0\" class=\"data row53 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col1\" class=\"data row53 col1\" >53</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col2\" class=\"data row53 col2\" >4439403</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col3\" class=\"data row53 col3\" >4535430</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col4\" class=\"data row53 col4\" >96027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row53_col5\" class=\"data row53 col5\" >2.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row54\" class=\"row_heading level0 row54\" >54</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col0\" class=\"data row54 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col1\" class=\"data row54 col1\" >54</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col2\" class=\"data row54 col2\" >4288447</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col3\" class=\"data row54 col3\" >4574760</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col4\" class=\"data row54 col4\" >286313</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row54_col5\" class=\"data row54 col5\" >6.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row55\" class=\"row_heading level0 row55\" >55</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col0\" class=\"data row55 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col1\" class=\"data row55 col1\" >55</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col2\" class=\"data row55 col2\" >4258970</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col3\" class=\"data row55 col3\" >4421856</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col4\" class=\"data row55 col4\" >162886</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row55_col5\" class=\"data row55 col5\" >3.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row56\" class=\"row_heading level0 row56\" >56</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col0\" class=\"data row56 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col1\" class=\"data row56 col1\" >56</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col2\" class=\"data row56 col2\" >4093136</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col3\" class=\"data row56 col3\" >4395949</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col4\" class=\"data row56 col4\" >302813</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row56_col5\" class=\"data row56 col5\" >7.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row57\" class=\"row_heading level0 row57\" >57</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col0\" class=\"data row57 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col1\" class=\"data row57 col1\" >57</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col2\" class=\"data row57 col2\" >3946518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col3\" class=\"data row57 col3\" >4347023</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col4\" class=\"data row57 col4\" >400505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row57_col5\" class=\"data row57 col5\" >10.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row58\" class=\"row_heading level0 row58\" >58</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col0\" class=\"data row58 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col1\" class=\"data row58 col1\" >58</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col2\" class=\"data row58 col2\" >3802447</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col3\" class=\"data row58 col3\" >4191360</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col4\" class=\"data row58 col4\" >388913</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row58_col5\" class=\"data row58 col5\" >10.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row59\" class=\"row_heading level0 row59\" >59</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col0\" class=\"data row59 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col1\" class=\"data row59 col1\" >59</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col2\" class=\"data row59 col2\" >3694254</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col3\" class=\"data row59 col3\" >4155521</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col4\" class=\"data row59 col4\" >461267</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row59_col5\" class=\"data row59 col5\" >12.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row60\" class=\"row_heading level0 row60\" >60</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col0\" class=\"data row60 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col1\" class=\"data row60 col1\" >60</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col2\" class=\"data row60 col2\" >3616721</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col3\" class=\"data row60 col3\" >3985598</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col4\" class=\"data row60 col4\" >368877</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row60_col5\" class=\"data row60 col5\" >10.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row61\" class=\"row_heading level0 row61\" >61</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col0\" class=\"data row61 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col1\" class=\"data row61 col1\" >61</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col2\" class=\"data row61 col2\" >3520109</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col3\" class=\"data row61 col3\" >3834367</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col4\" class=\"data row61 col4\" >314258</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row61_col5\" class=\"data row61 col5\" >8.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row62\" class=\"row_heading level0 row62\" >62</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col0\" class=\"data row62 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col1\" class=\"data row62 col1\" >62</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col2\" class=\"data row62 col2\" >3495059</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col3\" class=\"data row62 col3\" >3685282</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col4\" class=\"data row62 col4\" >190223</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row62_col5\" class=\"data row62 col5\" >5.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row63\" class=\"row_heading level0 row63\" >63</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col0\" class=\"data row63 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col1\" class=\"data row63 col1\" >63</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col2\" class=\"data row63 col2\" >3652167</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col3\" class=\"data row63 col3\" >3571610</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col4\" class=\"data row63 col4\" >-80557</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row63_col5\" class=\"data row63 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row64\" class=\"row_heading level0 row64\" >64</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col0\" class=\"data row64 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col1\" class=\"data row64 col1\" >64</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col2\" class=\"data row64 col2\" >2706055</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col3\" class=\"data row64 col3\" >3487559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col4\" class=\"data row64 col4\" >781504</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row64_col5\" class=\"data row64 col5\" >28.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row65\" class=\"row_heading level0 row65\" >65</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col0\" class=\"data row65 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col1\" class=\"data row65 col1\" >65</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col2\" class=\"data row65 col2\" >2678525</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col3\" class=\"data row65 col3\" >3382824</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col4\" class=\"data row65 col4\" >704299</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row65_col5\" class=\"data row65 col5\" >26.29%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row66\" class=\"row_heading level0 row66\" >66</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col0\" class=\"data row66 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col1\" class=\"data row66 col1\" >66</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col2\" class=\"data row66 col2\" >2621335</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col3\" class=\"data row66 col3\" >3347060</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col4\" class=\"data row66 col4\" >725725</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row66_col5\" class=\"data row66 col5\" >27.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row67\" class=\"row_heading level0 row67\" >67</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col0\" class=\"data row67 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col1\" class=\"data row67 col1\" >67</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col2\" class=\"data row67 col2\" >2693707</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col3\" class=\"data row67 col3\" >3485241</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col4\" class=\"data row67 col4\" >791534</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row67_col5\" class=\"data row67 col5\" >29.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row68\" class=\"row_heading level0 row68\" >68</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col0\" class=\"data row68 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col1\" class=\"data row68 col1\" >68</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col2\" class=\"data row68 col2\" >2359816</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col3\" class=\"data row68 col3\" >2572359</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col4\" class=\"data row68 col4\" >212543</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row68_col5\" class=\"data row68 col5\" >9.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row69\" class=\"row_heading level0 row69\" >69</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col0\" class=\"data row69 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col1\" class=\"data row69 col1\" >69</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col2\" class=\"data row69 col2\" >2167830</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col3\" class=\"data row69 col3\" >2534295</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col4\" class=\"data row69 col4\" >366465</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row69_col5\" class=\"data row69 col5\" >16.90%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row70\" class=\"row_heading level0 row70\" >70</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col0\" class=\"data row70 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col1\" class=\"data row70 col1\" >70</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col2\" class=\"data row70 col2\" >2062577</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col3\" class=\"data row70 col3\" >2465438</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col4\" class=\"data row70 col4\" >402861</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row70_col5\" class=\"data row70 col5\" >19.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row71\" class=\"row_heading level0 row71\" >71</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col0\" class=\"data row71 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col1\" class=\"data row71 col1\" >71</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col2\" class=\"data row71 col2\" >1953607</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col3\" class=\"data row71 col3\" >2519705</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col4\" class=\"data row71 col4\" >566098</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row71_col5\" class=\"data row71 col5\" >28.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row72\" class=\"row_heading level0 row72\" >72</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col0\" class=\"data row72 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col1\" class=\"data row72 col1\" >72</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col2\" class=\"data row72 col2\" >1883820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col3\" class=\"data row72 col3\" >2193945</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col4\" class=\"data row72 col4\" >310125</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row72_col5\" class=\"data row72 col5\" >16.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row73\" class=\"row_heading level0 row73\" >73</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col0\" class=\"data row73 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col1\" class=\"data row73 col1\" >73</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col2\" class=\"data row73 col2\" >1750304</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col3\" class=\"data row73 col3\" >2001700</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col4\" class=\"data row73 col4\" >251396</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row73_col5\" class=\"data row73 col5\" >14.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row74\" class=\"row_heading level0 row74\" >74</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col0\" class=\"data row74 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col1\" class=\"data row74 col1\" >74</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col2\" class=\"data row74 col2\" >1685995</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col3\" class=\"data row74 col3\" >1889513</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col4\" class=\"data row74 col4\" >203518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row74_col5\" class=\"data row74 col5\" >12.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row75\" class=\"row_heading level0 row75\" >75</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col0\" class=\"data row75 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col1\" class=\"data row75 col1\" >75</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col2\" class=\"data row75 col2\" >1631878</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col3\" class=\"data row75 col3\" >1773756</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col4\" class=\"data row75 col4\" >141878</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row75_col5\" class=\"data row75 col5\" >8.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row76\" class=\"row_heading level0 row76\" >76</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col0\" class=\"data row76 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col1\" class=\"data row76 col1\" >76</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col2\" class=\"data row76 col2\" >1481680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col3\" class=\"data row76 col3\" >1693674</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col4\" class=\"data row76 col4\" >211994</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row76_col5\" class=\"data row76 col5\" >14.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row77\" class=\"row_heading level0 row77\" >77</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col0\" class=\"data row77 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col1\" class=\"data row77 col1\" >77</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col2\" class=\"data row77 col2\" >1449173</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col3\" class=\"data row77 col3\" >1556104</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col4\" class=\"data row77 col4\" >106931</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row77_col5\" class=\"data row77 col5\" >7.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row78\" class=\"row_heading level0 row78\" >78</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col0\" class=\"data row78 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col1\" class=\"data row78 col1\" >78</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col2\" class=\"data row78 col2\" >1402182</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col3\" class=\"data row78 col3\" >1480611</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col4\" class=\"data row78 col4\" >78429</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row78_col5\" class=\"data row78 col5\" >5.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row79\" class=\"row_heading level0 row79\" >79</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col0\" class=\"data row79 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col1\" class=\"data row79 col1\" >79</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col2\" class=\"data row79 col2\" >1354912</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col3\" class=\"data row79 col3\" >1413193</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col4\" class=\"data row79 col4\" >58281</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row79_col5\" class=\"data row79 col5\" >4.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row80\" class=\"row_heading level0 row80\" >80</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col0\" class=\"data row80 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col1\" class=\"data row80 col1\" >80</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col2\" class=\"data row80 col2\" >1319725</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col3\" class=\"data row80 col3\" >1262537</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col4\" class=\"data row80 col4\" >-57188</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row80_col5\" class=\"data row80 col5\" >-4.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row81\" class=\"row_heading level0 row81\" >81</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col0\" class=\"data row81 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col1\" class=\"data row81 col1\" >81</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col2\" class=\"data row81 col2\" >1212603</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col3\" class=\"data row81 col3\" >1214357</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col4\" class=\"data row81 col4\" >1754</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row81_col5\" class=\"data row81 col5\" >0.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row82\" class=\"row_heading level0 row82\" >82</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col0\" class=\"data row82 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col1\" class=\"data row82 col1\" >82</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col2\" class=\"data row82 col2\" >1158351</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col3\" class=\"data row82 col3\" >1151677</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col4\" class=\"data row82 col4\" >-6674</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row82_col5\" class=\"data row82 col5\" >-0.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row83\" class=\"row_heading level0 row83\" >83</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col0\" class=\"data row83 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col1\" class=\"data row83 col1\" >83</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col2\" class=\"data row83 col2\" >1081440</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col3\" class=\"data row83 col3\" >1088601</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col4\" class=\"data row83 col4\" >7161</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row83_col5\" class=\"data row83 col5\" >0.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row84\" class=\"row_heading level0 row84\" >84</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col0\" class=\"data row84 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col1\" class=\"data row84 col1\" >84</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col2\" class=\"data row84 col2\" >987023</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col3\" class=\"data row84 col3\" >1034369</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col4\" class=\"data row84 col4\" >47346</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row84_col5\" class=\"data row84 col5\" >4.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row85\" class=\"row_heading level0 row85\" >85</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col0\" class=\"data row85 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col1\" class=\"data row85 col1\" >85</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col2\" class=\"data row85 col2\" >915013</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col3\" class=\"data row85 col3\" >922947</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col4\" class=\"data row85 col4\" >7934</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row85_col5\" class=\"data row85 col5\" >0.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row86\" class=\"row_heading level0 row86\" >86</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col0\" class=\"data row86 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col1\" class=\"data row86 col1\" >86</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col2\" class=\"data row86 col2\" >821549</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col3\" class=\"data row86 col3\" >853723</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col4\" class=\"data row86 col4\" >32174</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row86_col5\" class=\"data row86 col5\" >3.92%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row87\" class=\"row_heading level0 row87\" >87</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col0\" class=\"data row87 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col1\" class=\"data row87 col1\" >87</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col2\" class=\"data row87 col2\" >721196</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col3\" class=\"data row87 col3\" >768676</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col4\" class=\"data row87 col4\" >47480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row87_col5\" class=\"data row87 col5\" >6.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row88\" class=\"row_heading level0 row88\" >88</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col0\" class=\"data row88 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col1\" class=\"data row88 col1\" >88</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col2\" class=\"data row88 col2\" >636657</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col3\" class=\"data row88 col3\" >673402</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col4\" class=\"data row88 col4\" >36745</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row88_col5\" class=\"data row88 col5\" >5.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row89\" class=\"row_heading level0 row89\" >89</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col0\" class=\"data row89 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col1\" class=\"data row89 col1\" >89</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col2\" class=\"data row89 col2\" >546193</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col3\" class=\"data row89 col3\" >597828</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col4\" class=\"data row89 col4\" >51635</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row89_col5\" class=\"data row89 col5\" >9.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row90\" class=\"row_heading level0 row90\" >90</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col0\" class=\"data row90 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col1\" class=\"data row90 col1\" >90</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col2\" class=\"data row90 col2\" >448324</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col3\" class=\"data row90 col3\" >511074</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col4\" class=\"data row90 col4\" >62750</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row90_col5\" class=\"data row90 col5\" >14.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row91\" class=\"row_heading level0 row91\" >91</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col0\" class=\"data row91 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col1\" class=\"data row91 col1\" >91</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col2\" class=\"data row91 col2\" >344442</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col3\" class=\"data row91 col3\" >425314</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col4\" class=\"data row91 col4\" >80872</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row91_col5\" class=\"data row91 col5\" >23.48%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row92\" class=\"row_heading level0 row92\" >92</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col0\" class=\"data row92 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col1\" class=\"data row92 col1\" >92</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col2\" class=\"data row92 col2\" >288841</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col3\" class=\"data row92 col3\" >352912</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col4\" class=\"data row92 col4\" >64071</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row92_col5\" class=\"data row92 col5\" >22.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row93\" class=\"row_heading level0 row93\" >93</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col0\" class=\"data row93 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col1\" class=\"data row93 col1\" >93</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col2\" class=\"data row93 col2\" >219064</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col3\" class=\"data row93 col3\" >284885</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col4\" class=\"data row93 col4\" >65821</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row93_col5\" class=\"data row93 col5\" >30.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row94\" class=\"row_heading level0 row94\" >94</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col0\" class=\"data row94 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col1\" class=\"data row94 col1\" >94</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col2\" class=\"data row94 col2\" >170775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col3\" class=\"data row94 col3\" >217328</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col4\" class=\"data row94 col4\" >46553</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row94_col5\" class=\"data row94 col5\" >27.26%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row95\" class=\"row_heading level0 row95\" >95</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col0\" class=\"data row95 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col1\" class=\"data row95 col1\" >95</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col2\" class=\"data row95 col2\" >131077</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col3\" class=\"data row95 col3\" >156288</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col4\" class=\"data row95 col4\" >25211</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row95_col5\" class=\"data row95 col5\" >19.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row96\" class=\"row_heading level0 row96\" >96</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col0\" class=\"data row96 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col1\" class=\"data row96 col1\" >96</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col2\" class=\"data row96 col2\" >97161</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col3\" class=\"data row96 col3\" >120485</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col4\" class=\"data row96 col4\" >23324</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row96_col5\" class=\"data row96 col5\" >24.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row97\" class=\"row_heading level0 row97\" >97</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col0\" class=\"data row97 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col1\" class=\"data row97 col1\" >97</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col2\" class=\"data row97 col2\" >68893</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col3\" class=\"data row97 col3\" >83089</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col4\" class=\"data row97 col4\" >14196</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row97_col5\" class=\"data row97 col5\" >20.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row98\" class=\"row_heading level0 row98\" >98</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col0\" class=\"data row98 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col1\" class=\"data row98 col1\" >98</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col2\" class=\"data row98 col2\" >47037</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col3\" class=\"data row98 col3\" >59726</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col4\" class=\"data row98 col4\" >12689</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row98_col5\" class=\"data row98 col5\" >26.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row99\" class=\"row_heading level0 row99\" >99</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col0\" class=\"data row99 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col1\" class=\"data row99 col1\" >99</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col2\" class=\"data row99 col2\" >32178</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col3\" class=\"data row99 col3\" >41468</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col4\" class=\"data row99 col4\" >9290</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row99_col5\" class=\"data row99 col5\" >28.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row100\" class=\"row_heading level0 row100\" >100</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col0\" class=\"data row100 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col1\" class=\"data row100 col1\" >100</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col2\" class=\"data row100 col2\" >54410</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col3\" class=\"data row100 col3\" >71626</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col4\" class=\"data row100 col4\" >17216</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row100_col5\" class=\"data row100 col5\" >31.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row101\" class=\"row_heading level0 row101\" >101</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col0\" class=\"data row101 col0\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col1\" class=\"data row101 col1\" >999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col2\" class=\"data row101 col2\" >309346863</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col3\" class=\"data row101 col3\" >318907401</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col4\" class=\"data row101 col4\" >9560538</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row101_col5\" class=\"data row101 col5\" >3.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row102\" class=\"row_heading level0 row102\" >102</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col0\" class=\"data row102 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col1\" class=\"data row102 col1\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col2\" class=\"data row102 col2\" >2018420</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col3\" class=\"data row102 col3\" >2020326</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col4\" class=\"data row102 col4\" >1906</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row102_col5\" class=\"data row102 col5\" >0.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row103\" class=\"row_heading level0 row103\" >103</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col0\" class=\"data row103 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col1\" class=\"data row103 col1\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col2\" class=\"data row103 col2\" >2020332</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col3\" class=\"data row103 col3\" >2018401</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col4\" class=\"data row103 col4\" >-1931</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row103_col5\" class=\"data row103 col5\" >-0.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row104\" class=\"row_heading level0 row104\" >104</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col0\" class=\"data row104 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col1\" class=\"data row104 col1\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col2\" class=\"data row104 col2\" >2088685</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col3\" class=\"data row104 col3\" >2023673</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col4\" class=\"data row104 col4\" >-65012</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row104_col5\" class=\"data row104 col5\" >-3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row105\" class=\"row_heading level0 row105\" >105</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col0\" class=\"data row105 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col1\" class=\"data row105 col1\" >3</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col2\" class=\"data row105 col2\" >2101272</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col3\" class=\"data row105 col3\" >2049596</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col4\" class=\"data row105 col4\" >-51676</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row105_col5\" class=\"data row105 col5\" >-2.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row106\" class=\"row_heading level0 row106\" >106</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col0\" class=\"data row106 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col1\" class=\"data row106 col1\" >4</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col2\" class=\"data row106 col2\" >2084312</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col3\" class=\"data row106 col3\" >2044517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col4\" class=\"data row106 col4\" >-39795</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row106_col5\" class=\"data row106 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row107\" class=\"row_heading level0 row107\" >107</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col0\" class=\"data row107 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col1\" class=\"data row107 col1\" >5</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col2\" class=\"data row107 col2\" >2076573</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col3\" class=\"data row107 col3\" >2044339</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col4\" class=\"data row107 col4\" >-32234</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row107_col5\" class=\"data row107 col5\" >-1.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row108\" class=\"row_heading level0 row108\" >108</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col0\" class=\"data row108 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col1\" class=\"data row108 col1\" >6</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col2\" class=\"data row108 col2\" >2079410</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col3\" class=\"data row108 col3\" >2111060</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col4\" class=\"data row108 col4\" >31650</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row108_col5\" class=\"data row108 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row109\" class=\"row_heading level0 row109\" >109</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col0\" class=\"data row109 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col1\" class=\"data row109 col1\" >7</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col2\" class=\"data row109 col2\" >2063139</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col3\" class=\"data row109 col3\" >2122832</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col4\" class=\"data row109 col4\" >59693</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row109_col5\" class=\"data row109 col5\" >2.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row110\" class=\"row_heading level0 row110\" >110</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col0\" class=\"data row110 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col1\" class=\"data row110 col1\" >8</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col2\" class=\"data row110 col2\" >2054462</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col3\" class=\"data row110 col3\" >2105618</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col4\" class=\"data row110 col4\" >51156</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row110_col5\" class=\"data row110 col5\" >2.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row111\" class=\"row_heading level0 row111\" >111</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col0\" class=\"data row111 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col1\" class=\"data row111 col1\" >9</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col2\" class=\"data row111 col2\" >2107037</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col3\" class=\"data row111 col3\" >2097690</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col4\" class=\"data row111 col4\" >-9347</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row111_col5\" class=\"data row111 col5\" >-0.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row112\" class=\"row_heading level0 row112\" >112</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col0\" class=\"data row112 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col1\" class=\"data row112 col1\" >10</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col2\" class=\"data row112 col2\" >2142167</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col3\" class=\"data row112 col3\" >2100262</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col4\" class=\"data row112 col4\" >-41905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row112_col5\" class=\"data row112 col5\" >-1.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row113\" class=\"row_heading level0 row113\" >113</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col0\" class=\"data row113 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col1\" class=\"data row113 col1\" >11</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col2\" class=\"data row113 col2\" >2104797</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col3\" class=\"data row113 col3\" >2084169</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col4\" class=\"data row113 col4\" >-20628</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row113_col5\" class=\"data row113 col5\" >-0.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row114\" class=\"row_heading level0 row114\" >114</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col0\" class=\"data row114 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col1\" class=\"data row114 col1\" >12</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col2\" class=\"data row114 col2\" >2103649</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col3\" class=\"data row114 col3\" >2075836</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col4\" class=\"data row114 col4\" >-27813</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row114_col5\" class=\"data row114 col5\" >-1.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row115\" class=\"row_heading level0 row115\" >115</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col0\" class=\"data row115 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col1\" class=\"data row115 col1\" >13</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col2\" class=\"data row115 col2\" >2104949</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col3\" class=\"data row115 col3\" >2128914</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col4\" class=\"data row115 col4\" >23965</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row115_col5\" class=\"data row115 col5\" >1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row116\" class=\"row_heading level0 row116\" >116</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col0\" class=\"data row116 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col1\" class=\"data row116 col1\" >14</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col2\" class=\"data row116 col2\" >2122913</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col3\" class=\"data row116 col3\" >2164924</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col4\" class=\"data row116 col4\" >42011</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row116_col5\" class=\"data row116 col5\" >1.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row117\" class=\"row_heading level0 row117\" >117</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col0\" class=\"data row117 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col1\" class=\"data row117 col1\" >15</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col2\" class=\"data row117 col2\" >2170442</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col3\" class=\"data row117 col3\" >2129062</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col4\" class=\"data row117 col4\" >-41380</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row117_col5\" class=\"data row117 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row118\" class=\"row_heading level0 row118\" >118</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col0\" class=\"data row118 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col1\" class=\"data row118 col1\" >16</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col2\" class=\"data row118 col2\" >2215032</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col3\" class=\"data row118 col3\" >2131425</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col4\" class=\"data row118 col4\" >-83607</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row118_col5\" class=\"data row118 col5\" >-3.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row119\" class=\"row_heading level0 row119\" >119</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col0\" class=\"data row119 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col1\" class=\"data row119 col1\" >17</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col2\" class=\"data row119 col2\" >2252838</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col3\" class=\"data row119 col3\" >2139361</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col4\" class=\"data row119 col4\" >-113477</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row119_col5\" class=\"data row119 col5\" >-5.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row120\" class=\"row_heading level0 row120\" >120</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col0\" class=\"data row120 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col1\" class=\"data row120 col1\" >18</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col2\" class=\"data row120 col2\" >2305733</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col3\" class=\"data row120 col3\" >2165744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col4\" class=\"data row120 col4\" >-139989</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row120_col5\" class=\"data row120 col5\" >-6.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row121\" class=\"row_heading level0 row121\" >121</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col0\" class=\"data row121 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col1\" class=\"data row121 col1\" >19</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col2\" class=\"data row121 col2\" >2334906</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col3\" class=\"data row121 col3\" >2221910</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col4\" class=\"data row121 col4\" >-112996</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row121_col5\" class=\"data row121 col5\" >-4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row122\" class=\"row_heading level0 row122\" >122</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col0\" class=\"data row122 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col1\" class=\"data row122 col1\" >20</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col2\" class=\"data row122 col2\" >2331845</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col3\" class=\"data row122 col3\" >2271216</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col4\" class=\"data row122 col4\" >-60629</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row122_col5\" class=\"data row122 col5\" >-2.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row123\" class=\"row_heading level0 row123\" >123</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col0\" class=\"data row123 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col1\" class=\"data row123 col1\" >21</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col2\" class=\"data row123 col2\" >2241083</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col3\" class=\"data row123 col3\" >2312917</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col4\" class=\"data row123 col4\" >71834</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row123_col5\" class=\"data row123 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row124\" class=\"row_heading level0 row124\" >124</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col0\" class=\"data row124 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col1\" class=\"data row124 col1\" >22</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col2\" class=\"data row124 col2\" >2188199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col3\" class=\"data row124 col3\" >2370459</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col4\" class=\"data row124 col4\" >182260</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row124_col5\" class=\"data row124 col5\" >8.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row125\" class=\"row_heading level0 row125\" >125</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col0\" class=\"data row125 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col1\" class=\"data row125 col1\" >23</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col2\" class=\"data row125 col2\" >2151068</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col3\" class=\"data row125 col3\" >2402294</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col4\" class=\"data row125 col4\" >251226</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row125_col5\" class=\"data row125 col5\" >11.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row126\" class=\"row_heading level0 row126\" >126</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col0\" class=\"data row126 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col1\" class=\"data row126 col1\" >24</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col2\" class=\"data row126 col2\" >2161347</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col3\" class=\"data row126 col3\" >2393037</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col4\" class=\"data row126 col4\" >231690</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row126_col5\" class=\"data row126 col5\" >10.72%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row127\" class=\"row_heading level0 row127\" >127</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col0\" class=\"data row127 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col1\" class=\"data row127 col1\" >25</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col2\" class=\"data row127 col2\" >2177131</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col3\" class=\"data row127 col3\" >2296875</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col4\" class=\"data row127 col4\" >119744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row127_col5\" class=\"data row127 col5\" >5.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row128\" class=\"row_heading level0 row128\" >128</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col0\" class=\"data row128 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col1\" class=\"data row128 col1\" >26</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col2\" class=\"data row128 col2\" >2102331</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col3\" class=\"data row128 col3\" >2240881</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col4\" class=\"data row128 col4\" >138550</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row128_col5\" class=\"data row128 col5\" >6.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row129\" class=\"row_heading level0 row129\" >129</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col0\" class=\"data row129 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col1\" class=\"data row129 col1\" >27</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col2\" class=\"data row129 col2\" >2135178</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col3\" class=\"data row129 col3\" >2201518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col4\" class=\"data row129 col4\" >66340</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row129_col5\" class=\"data row129 col5\" >3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row130\" class=\"row_heading level0 row130\" >130</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col0\" class=\"data row130 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col1\" class=\"data row130 col1\" >28</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col2\" class=\"data row130 col2\" >2134981</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col3\" class=\"data row130 col3\" >2208749</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col4\" class=\"data row130 col4\" >73768</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row130_col5\" class=\"data row130 col5\" >3.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row131\" class=\"row_heading level0 row131\" >131</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col0\" class=\"data row131 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col1\" class=\"data row131 col1\" >29</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col2\" class=\"data row131 col2\" >2112313</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col3\" class=\"data row131 col3\" >2219872</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col4\" class=\"data row131 col4\" >107559</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row131_col5\" class=\"data row131 col5\" >5.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row132\" class=\"row_heading level0 row132\" >132</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col0\" class=\"data row132 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col1\" class=\"data row132 col1\" >30</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col2\" class=\"data row132 col2\" >2167495</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col3\" class=\"data row132 col3\" >2142240</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col4\" class=\"data row132 col4\" >-25255</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row132_col5\" class=\"data row132 col5\" >-1.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row133\" class=\"row_heading level0 row133\" >133</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col0\" class=\"data row133 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col1\" class=\"data row133 col1\" >31</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col2\" class=\"data row133 col2\" >2026439</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col3\" class=\"data row133 col3\" >2171839</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col4\" class=\"data row133 col4\" >145400</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row133_col5\" class=\"data row133 col5\" >7.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row134\" class=\"row_heading level0 row134\" >134</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col0\" class=\"data row134 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col1\" class=\"data row134 col1\" >32</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col2\" class=\"data row134 col2\" >1986147</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col3\" class=\"data row134 col3\" >2167557</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col4\" class=\"data row134 col4\" >181410</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row134_col5\" class=\"data row134 col5\" >9.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row135\" class=\"row_heading level0 row135\" >135</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col0\" class=\"data row135 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col1\" class=\"data row135 col1\" >33</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col2\" class=\"data row135 col2\" >1963645</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col3\" class=\"data row135 col3\" >2141552</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col4\" class=\"data row135 col4\" >177907</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row135_col5\" class=\"data row135 col5\" >9.06%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row136\" class=\"row_heading level0 row136\" >136</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col0\" class=\"data row136 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col1\" class=\"data row136 col1\" >34</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col2\" class=\"data row136 col2\" >1908731</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col3\" class=\"data row136 col3\" >2192877</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col4\" class=\"data row136 col4\" >284146</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row136_col5\" class=\"data row136 col5\" >14.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row137\" class=\"row_heading level0 row137\" >137</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col0\" class=\"data row137 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col1\" class=\"data row137 col1\" >35</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col2\" class=\"data row137 col2\" >1974636</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col3\" class=\"data row137 col3\" >2047877</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col4\" class=\"data row137 col4\" >73241</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row137_col5\" class=\"data row137 col5\" >3.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row138\" class=\"row_heading level0 row138\" >138</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col0\" class=\"data row138 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col1\" class=\"data row138 col1\" >36</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col2\" class=\"data row138 col2\" >1907408</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col3\" class=\"data row138 col3\" >2005880</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col4\" class=\"data row138 col4\" >98472</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row138_col5\" class=\"data row138 col5\" >5.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row139\" class=\"row_heading level0 row139\" >139</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col0\" class=\"data row139 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col1\" class=\"data row139 col1\" >37</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col2\" class=\"data row139 col2\" >1934537</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col3\" class=\"data row139 col3\" >1979888</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col4\" class=\"data row139 col4\" >45351</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row139_col5\" class=\"data row139 col5\" >2.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row140\" class=\"row_heading level0 row140\" >140</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col0\" class=\"data row140 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col1\" class=\"data row140 col1\" >38</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col2\" class=\"data row140 col2\" >2028052</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col3\" class=\"data row140 col3\" >1923133</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col4\" class=\"data row140 col4\" >-104919</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row140_col5\" class=\"data row140 col5\" >-5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row141\" class=\"row_heading level0 row141\" >141</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col0\" class=\"data row141 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col1\" class=\"data row141 col1\" >39</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col2\" class=\"data row141 col2\" >2148718</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col3\" class=\"data row141 col3\" >1986712</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col4\" class=\"data row141 col4\" >-162006</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row141_col5\" class=\"data row141 col5\" >-7.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row142\" class=\"row_heading level0 row142\" >142</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col0\" class=\"data row142 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col1\" class=\"data row142 col1\" >40</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col2\" class=\"data row142 col2\" >2189516</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col3\" class=\"data row142 col3\" >1917201</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col4\" class=\"data row142 col4\" >-272315</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row142_col5\" class=\"data row142 col5\" >-12.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row143\" class=\"row_heading level0 row143\" >143</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col0\" class=\"data row143 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col1\" class=\"data row143 col1\" >41</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col2\" class=\"data row143 col2\" >2073902</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col3\" class=\"data row143 col3\" >1941203</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col4\" class=\"data row143 col4\" >-132699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row143_col5\" class=\"data row143 col5\" >-6.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row144\" class=\"row_heading level0 row144\" >144</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col0\" class=\"data row144 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col1\" class=\"data row144 col1\" >42</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col2\" class=\"data row144 col2\" >2031782</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col3\" class=\"data row144 col3\" >2032207</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col4\" class=\"data row144 col4\" >425</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row144_col5\" class=\"data row144 col5\" >0.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row145\" class=\"row_heading level0 row145\" >145</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col0\" class=\"data row145 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col1\" class=\"data row145 col1\" >43</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col2\" class=\"data row145 col2\" >2030982</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col3\" class=\"data row145 col3\" >2147960</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col4\" class=\"data row145 col4\" >116978</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row145_col5\" class=\"data row145 col5\" >5.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row146\" class=\"row_heading level0 row146\" >146</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col0\" class=\"data row146 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col1\" class=\"data row146 col1\" >44</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col2\" class=\"data row146 col2\" >2074572</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col3\" class=\"data row146 col3\" >2184448</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col4\" class=\"data row146 col4\" >109876</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row146_col5\" class=\"data row146 col5\" >5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row147\" class=\"row_heading level0 row147\" >147</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col0\" class=\"data row147 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col1\" class=\"data row147 col1\" >45</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col2\" class=\"data row147 col2\" >2201905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col3\" class=\"data row147 col3\" >2067426</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col4\" class=\"data row147 col4\" >-134479</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row147_col5\" class=\"data row147 col5\" >-6.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row148\" class=\"row_heading level0 row148\" >148</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col0\" class=\"data row148 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col1\" class=\"data row148 col1\" >46</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col2\" class=\"data row148 col2\" >2238774</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col3\" class=\"data row148 col3\" >2023033</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col4\" class=\"data row148 col4\" >-215741</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row148_col5\" class=\"data row148 col5\" >-9.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row149\" class=\"row_heading level0 row149\" >149</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col0\" class=\"data row149 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col1\" class=\"data row149 col1\" >47</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col2\" class=\"data row149 col2\" >2237940</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col3\" class=\"data row149 col3\" >2019517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col4\" class=\"data row149 col4\" >-218423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row149_col5\" class=\"data row149 col5\" >-9.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row150\" class=\"row_heading level0 row150\" >150</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col0\" class=\"data row150 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col1\" class=\"data row150 col1\" >48</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col2\" class=\"data row150 col2\" >2235296</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col3\" class=\"data row150 col3\" >2058392</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col4\" class=\"data row150 col4\" >-176904</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row150_col5\" class=\"data row150 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row151\" class=\"row_heading level0 row151\" >151</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col0\" class=\"data row151 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col1\" class=\"data row151 col1\" >49</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col2\" class=\"data row151 col2\" >2262458</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col3\" class=\"data row151 col3\" >2180214</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col4\" class=\"data row151 col4\" >-82244</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row151_col5\" class=\"data row151 col5\" >-3.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row152\" class=\"row_heading level0 row152\" >152</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col0\" class=\"data row152 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col1\" class=\"data row152 col1\" >50</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col2\" class=\"data row152 col2\" >2290862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col3\" class=\"data row152 col3\" >2211767</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col4\" class=\"data row152 col4\" >-79095</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row152_col5\" class=\"data row152 col5\" >-3.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row153\" class=\"row_heading level0 row153\" >153</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col0\" class=\"data row153 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col1\" class=\"data row153 col1\" >51</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col2\" class=\"data row153 col2\" >2209780</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col3\" class=\"data row153 col3\" >2205399</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col4\" class=\"data row153 col4\" >-4381</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row153_col5\" class=\"data row153 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row154\" class=\"row_heading level0 row154\" >154</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col0\" class=\"data row154 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col1\" class=\"data row154 col1\" >52</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col2\" class=\"data row154 col2\" >2197161</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col3\" class=\"data row154 col3\" >2197801</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col4\" class=\"data row154 col4\" >640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row154_col5\" class=\"data row154 col5\" >0.03%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row155\" class=\"row_heading level0 row155\" >155</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col0\" class=\"data row155 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col1\" class=\"data row155 col1\" >53</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col2\" class=\"data row155 col2\" >2170923</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col3\" class=\"data row155 col3\" >2219328</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col4\" class=\"data row155 col4\" >48405</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row155_col5\" class=\"data row155 col5\" >2.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row156\" class=\"row_heading level0 row156\" >156</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col0\" class=\"data row156 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col1\" class=\"data row156 col1\" >54</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col2\" class=\"data row156 col2\" >2091640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col3\" class=\"data row156 col3\" >2242757</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col4\" class=\"data row156 col4\" >151117</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row156_col5\" class=\"data row156 col5\" >7.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row157\" class=\"row_heading level0 row157\" >157</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col0\" class=\"data row157 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col1\" class=\"data row157 col1\" >55</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col2\" class=\"data row157 col2\" >2075199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col3\" class=\"data row157 col3\" >2158427</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col4\" class=\"data row157 col4\" >83228</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row157_col5\" class=\"data row157 col5\" >4.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row158\" class=\"row_heading level0 row158\" >158</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col0\" class=\"data row158 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col1\" class=\"data row158 col1\" >56</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col2\" class=\"data row158 col2\" >1984452</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col3\" class=\"data row158 col3\" >2140940</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col4\" class=\"data row158 col4\" >156488</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row158_col5\" class=\"data row158 col5\" >7.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row159\" class=\"row_heading level0 row159\" >159</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col0\" class=\"data row159 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col1\" class=\"data row159 col1\" >57</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col2\" class=\"data row159 col2\" >1909997</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col3\" class=\"data row159 col3\" >2109804</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col4\" class=\"data row159 col4\" >199807</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row159_col5\" class=\"data row159 col5\" >10.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row160\" class=\"row_heading level0 row160\" >160</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col0\" class=\"data row160 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col1\" class=\"data row160 col1\" >58</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col2\" class=\"data row160 col2\" >1838680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col3\" class=\"data row160 col3\" >2027452</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col4\" class=\"data row160 col4\" >188772</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row160_col5\" class=\"data row160 col5\" >10.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row161\" class=\"row_heading level0 row161\" >161</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col0\" class=\"data row161 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col1\" class=\"data row161 col1\" >59</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col2\" class=\"data row161 col2\" >1779480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col3\" class=\"data row161 col3\" >2006587</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col4\" class=\"data row161 col4\" >227107</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row161_col5\" class=\"data row161 col5\" >12.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row162\" class=\"row_heading level0 row162\" >162</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col0\" class=\"data row162 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col1\" class=\"data row162 col1\" >60</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col2\" class=\"data row162 col2\" >1742220</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col3\" class=\"data row162 col3\" >1913729</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col4\" class=\"data row162 col4\" >171509</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row162_col5\" class=\"data row162 col5\" >9.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row163\" class=\"row_heading level0 row163\" >163</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col0\" class=\"data row163 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col1\" class=\"data row163 col1\" >61</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col2\" class=\"data row163 col2\" >1691401</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col3\" class=\"data row163 col3\" >1836656</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col4\" class=\"data row163 col4\" >145255</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row163_col5\" class=\"data row163 col5\" >8.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row164\" class=\"row_heading level0 row164\" >164</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col0\" class=\"data row164 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col1\" class=\"data row164 col1\" >62</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col2\" class=\"data row164 col2\" >1679060</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col3\" class=\"data row164 col3\" >1762880</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col4\" class=\"data row164 col4\" >83820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row164_col5\" class=\"data row164 col5\" >4.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row165\" class=\"row_heading level0 row165\" >165</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col0\" class=\"data row165 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col1\" class=\"data row165 col1\" >63</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col2\" class=\"data row165 col2\" >1753903</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col3\" class=\"data row165 col3\" >1701014</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col4\" class=\"data row165 col4\" >-52889</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row165_col5\" class=\"data row165 col5\" >-3.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row166\" class=\"row_heading level0 row166\" >166</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col0\" class=\"data row166 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col1\" class=\"data row166 col1\" >64</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col2\" class=\"data row166 col2\" >1291833</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col3\" class=\"data row166 col3\" >1660815</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col4\" class=\"data row166 col4\" >368982</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row166_col5\" class=\"data row166 col5\" >28.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row167\" class=\"row_heading level0 row167\" >167</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col0\" class=\"data row167 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col1\" class=\"data row167 col1\" >65</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col2\" class=\"data row167 col2\" >1272686</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col3\" class=\"data row167 col3\" >1606772</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col4\" class=\"data row167 col4\" >334086</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row167_col5\" class=\"data row167 col5\" >26.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row168\" class=\"row_heading level0 row168\" >168</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col0\" class=\"data row168 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col1\" class=\"data row168 col1\" >66</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col2\" class=\"data row168 col2\" >1239794</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col3\" class=\"data row168 col3\" >1588723</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col4\" class=\"data row168 col4\" >348929</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row168_col5\" class=\"data row168 col5\" >28.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row169\" class=\"row_heading level0 row169\" >169</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col0\" class=\"data row169 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col1\" class=\"data row169 col1\" >67</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col2\" class=\"data row169 col2\" >1270145</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col3\" class=\"data row169 col3\" >1652998</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col4\" class=\"data row169 col4\" >382853</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row169_col5\" class=\"data row169 col5\" >30.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row170\" class=\"row_heading level0 row170\" >170</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col0\" class=\"data row170 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col1\" class=\"data row170 col1\" >68</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col2\" class=\"data row170 col2\" >1105699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col3\" class=\"data row170 col3\" >1211278</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col4\" class=\"data row170 col4\" >105579</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row170_col5\" class=\"data row170 col5\" >9.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row171\" class=\"row_heading level0 row171\" >171</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col0\" class=\"data row171 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col1\" class=\"data row171 col1\" >69</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col2\" class=\"data row171 col2\" >1006782</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col3\" class=\"data row171 col3\" >1186872</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col4\" class=\"data row171 col4\" >180090</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row171_col5\" class=\"data row171 col5\" >17.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row172\" class=\"row_heading level0 row172\" >172</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col0\" class=\"data row172 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col1\" class=\"data row172 col1\" >70</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col2\" class=\"data row172 col2\" >954073</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col3\" class=\"data row172 col3\" >1148508</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col4\" class=\"data row172 col4\" >194435</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row172_col5\" class=\"data row172 col5\" >20.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row173\" class=\"row_heading level0 row173\" >173</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col0\" class=\"data row173 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col1\" class=\"data row173 col1\" >71</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col2\" class=\"data row173 col2\" >903258</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col3\" class=\"data row173 col3\" >1169115</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col4\" class=\"data row173 col4\" >265857</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row173_col5\" class=\"data row173 col5\" >29.43%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row174\" class=\"row_heading level0 row174\" >174</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col0\" class=\"data row174 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col1\" class=\"data row174 col1\" >72</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col2\" class=\"data row174 col2\" >862529</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col3\" class=\"data row174 col3\" >1010582</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col4\" class=\"data row174 col4\" >148053</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row174_col5\" class=\"data row174 col5\" >17.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row175\" class=\"row_heading level0 row175\" >175</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col0\" class=\"data row175 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col1\" class=\"data row175 col1\" >73</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col2\" class=\"data row175 col2\" >794646</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col3\" class=\"data row175 col3\" >912673</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col4\" class=\"data row175 col4\" >118027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row175_col5\" class=\"data row175 col5\" >14.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row176\" class=\"row_heading level0 row176\" >176</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col0\" class=\"data row176 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col1\" class=\"data row176 col1\" >74</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col2\" class=\"data row176 col2\" >758830</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col3\" class=\"data row176 col3\" >856970</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col4\" class=\"data row176 col4\" >98140</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row176_col5\" class=\"data row176 col5\" >12.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row177\" class=\"row_heading level0 row177\" >177</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col0\" class=\"data row177 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col1\" class=\"data row177 col1\" >75</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col2\" class=\"data row177 col2\" >725663</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col3\" class=\"data row177 col3\" >802960</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col4\" class=\"data row177 col4\" >77297</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row177_col5\" class=\"data row177 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row178\" class=\"row_heading level0 row178\" >178</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col0\" class=\"data row178 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col1\" class=\"data row178 col1\" >76</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col2\" class=\"data row178 col2\" >653551</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col3\" class=\"data row178 col3\" >757841</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col4\" class=\"data row178 col4\" >104290</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row178_col5\" class=\"data row178 col5\" >15.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row179\" class=\"row_heading level0 row179\" >179</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col0\" class=\"data row179 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col1\" class=\"data row179 col1\" >77</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col2\" class=\"data row179 col2\" >630867</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col3\" class=\"data row179 col3\" >689162</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col4\" class=\"data row179 col4\" >58295</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row179_col5\" class=\"data row179 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row180\" class=\"row_heading level0 row180\" >180</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col0\" class=\"data row180 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col1\" class=\"data row180 col1\" >78</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col2\" class=\"data row180 col2\" >602774</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col3\" class=\"data row180 col3\" >648696</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col4\" class=\"data row180 col4\" >45922</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row180_col5\" class=\"data row180 col5\" >7.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row181\" class=\"row_heading level0 row181\" >181</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col0\" class=\"data row181 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col1\" class=\"data row181 col1\" >79</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col2\" class=\"data row181 col2\" >573885</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col3\" class=\"data row181 col3\" >610115</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col4\" class=\"data row181 col4\" >36230</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row181_col5\" class=\"data row181 col5\" >6.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row182\" class=\"row_heading level0 row182\" >182</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col0\" class=\"data row182 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col1\" class=\"data row182 col1\" >80</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col2\" class=\"data row182 col2\" >549216</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col3\" class=\"data row182 col3\" >539227</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col4\" class=\"data row182 col4\" >-9989</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row182_col5\" class=\"data row182 col5\" >-1.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row183\" class=\"row_heading level0 row183\" >183</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col0\" class=\"data row183 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col1\" class=\"data row183 col1\" >81</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col2\" class=\"data row183 col2\" >496070</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col3\" class=\"data row183 col3\" >510305</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col4\" class=\"data row183 col4\" >14235</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row183_col5\" class=\"data row183 col5\" >2.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row184\" class=\"row_heading level0 row184\" >184</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col0\" class=\"data row184 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col1\" class=\"data row184 col1\" >82</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col2\" class=\"data row184 col2\" >462807</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col3\" class=\"data row184 col3\" >476034</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col4\" class=\"data row184 col4\" >13227</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row184_col5\" class=\"data row184 col5\" >2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row185\" class=\"row_heading level0 row185\" >185</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col0\" class=\"data row185 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col1\" class=\"data row185 col1\" >83</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col2\" class=\"data row185 col2\" >422999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col3\" class=\"data row185 col3\" >441530</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col4\" class=\"data row185 col4\" >18531</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row185_col5\" class=\"data row185 col5\" >4.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row186\" class=\"row_heading level0 row186\" >186</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col0\" class=\"data row186 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col1\" class=\"data row186 col1\" >84</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col2\" class=\"data row186 col2\" >375685</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col3\" class=\"data row186 col3\" >410385</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col4\" class=\"data row186 col4\" >34700</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row186_col5\" class=\"data row186 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row187\" class=\"row_heading level0 row187\" >187</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col0\" class=\"data row187 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col1\" class=\"data row187 col1\" >85</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col2\" class=\"data row187 col2\" >337661</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col3\" class=\"data row187 col3\" >358342</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col4\" class=\"data row187 col4\" >20681</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row187_col5\" class=\"data row187 col5\" >6.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row188\" class=\"row_heading level0 row188\" >188</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col0\" class=\"data row188 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col1\" class=\"data row188 col1\" >86</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col2\" class=\"data row188 col2\" >295396</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col3\" class=\"data row188 col3\" >322043</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col4\" class=\"data row188 col4\" >26647</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row188_col5\" class=\"data row188 col5\" >9.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row189\" class=\"row_heading level0 row189\" >189</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col0\" class=\"data row189 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col1\" class=\"data row189 col1\" >87</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col2\" class=\"data row189 col2\" >253621</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col3\" class=\"data row189 col3\" >282423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col4\" class=\"data row189 col4\" >28802</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row189_col5\" class=\"data row189 col5\" >11.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row190\" class=\"row_heading level0 row190\" >190</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col0\" class=\"data row190 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col1\" class=\"data row190 col1\" >88</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col2\" class=\"data row190 col2\" >216220</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col3\" class=\"data row190 col3\" >239455</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col4\" class=\"data row190 col4\" >23235</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row190_col5\" class=\"data row190 col5\" >10.75%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row191\" class=\"row_heading level0 row191\" >191</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col0\" class=\"data row191 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col1\" class=\"data row191 col1\" >89</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col2\" class=\"data row191 col2\" >180461</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col3\" class=\"data row191 col3\" >204850</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col4\" class=\"data row191 col4\" >24389</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row191_col5\" class=\"data row191 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row192\" class=\"row_heading level0 row192\" >192</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col0\" class=\"data row192 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col1\" class=\"data row192 col1\" >90</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col2\" class=\"data row192 col2\" >141399</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col3\" class=\"data row192 col3\" >169644</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col4\" class=\"data row192 col4\" >28245</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row192_col5\" class=\"data row192 col5\" >19.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row193\" class=\"row_heading level0 row193\" >193</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col0\" class=\"data row193 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col1\" class=\"data row193 col1\" >91</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col2\" class=\"data row193 col2\" >104291</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col3\" class=\"data row193 col3\" >137425</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col4\" class=\"data row193 col4\" >33134</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row193_col5\" class=\"data row193 col5\" >31.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row194\" class=\"row_heading level0 row194\" >194</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col0\" class=\"data row194 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col1\" class=\"data row194 col1\" >92</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col2\" class=\"data row194 col2\" >83462</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col3\" class=\"data row194 col3\" >109264</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col4\" class=\"data row194 col4\" >25802</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row194_col5\" class=\"data row194 col5\" >30.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row195\" class=\"row_heading level0 row195\" >195</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col0\" class=\"data row195 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col1\" class=\"data row195 col1\" >93</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col2\" class=\"data row195 col2\" >60182</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col3\" class=\"data row195 col3\" >85459</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col4\" class=\"data row195 col4\" >25277</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row195_col5\" class=\"data row195 col5\" >42.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row196\" class=\"row_heading level0 row196\" >196</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col0\" class=\"data row196 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col1\" class=\"data row196 col1\" >94</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col2\" class=\"data row196 col2\" >43827</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col3\" class=\"data row196 col3\" >61691</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col4\" class=\"data row196 col4\" >17864</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row196_col5\" class=\"data row196 col5\" >40.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row197\" class=\"row_heading level0 row197\" >197</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col0\" class=\"data row197 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col1\" class=\"data row197 col1\" >95</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col2\" class=\"data row197 col2\" >31736</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col3\" class=\"data row197 col3\" >42556</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col4\" class=\"data row197 col4\" >10820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row197_col5\" class=\"data row197 col5\" >34.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row198\" class=\"row_heading level0 row198\" >198</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col0\" class=\"data row198 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col1\" class=\"data row198 col1\" >96</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col2\" class=\"data row198 col2\" >22022</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col3\" class=\"data row198 col3\" >31053</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col4\" class=\"data row198 col4\" >9031</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row198_col5\" class=\"data row198 col5\" >41.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row199\" class=\"row_heading level0 row199\" >199</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col0\" class=\"data row199 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col1\" class=\"data row199 col1\" >97</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col2\" class=\"data row199 col2\" >14775</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col3\" class=\"data row199 col3\" >20310</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col4\" class=\"data row199 col4\" >5535</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row199_col5\" class=\"data row199 col5\" >37.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row200\" class=\"row_heading level0 row200\" >200</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col0\" class=\"data row200 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col1\" class=\"data row200 col1\" >98</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col2\" class=\"data row200 col2\" >9505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col3\" class=\"data row200 col3\" >13518</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col4\" class=\"data row200 col4\" >4013</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row200_col5\" class=\"data row200 col5\" >42.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row201\" class=\"row_heading level0 row201\" >201</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col0\" class=\"data row201 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col1\" class=\"data row201 col1\" >99</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col2\" class=\"data row201 col2\" >6104</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col3\" class=\"data row201 col3\" >8951</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col4\" class=\"data row201 col4\" >2847</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row201_col5\" class=\"data row201 col5\" >46.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row202\" class=\"row_heading level0 row202\" >202</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col0\" class=\"data row202 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col1\" class=\"data row202 col1\" >100</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col2\" class=\"data row202 col2\" >9352</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col3\" class=\"data row202 col3\" >13618</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col4\" class=\"data row202 col4\" >4266</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row202_col5\" class=\"data row202 col5\" >45.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row203\" class=\"row_heading level0 row203\" >203</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col0\" class=\"data row203 col0\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col1\" class=\"data row203 col1\" >999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col2\" class=\"data row203 col2\" >152088043</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col3\" class=\"data row203 col3\" >156955337</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col4\" class=\"data row203 col4\" >4867294</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row203_col5\" class=\"data row203 col5\" >3.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row204\" class=\"row_heading level0 row204\" >204</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col0\" class=\"data row204 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col1\" class=\"data row204 col1\" >0</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col2\" class=\"data row204 col2\" >1932910</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col3\" class=\"data row204 col3\" >1929449</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col4\" class=\"data row204 col4\" >-3461</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row204_col5\" class=\"data row204 col5\" >-0.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row205\" class=\"row_heading level0 row205\" >205</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col0\" class=\"data row205 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col1\" class=\"data row205 col1\" >1</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col2\" class=\"data row205 col2\" >1937556</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col3\" class=\"data row205 col3\" >1931375</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col4\" class=\"data row205 col4\" >-6181</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row205_col5\" class=\"data row205 col5\" >-0.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row206\" class=\"row_heading level0 row206\" >206</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col0\" class=\"data row206 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col1\" class=\"data row206 col1\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col2\" class=\"data row206 col2\" >2002177</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col3\" class=\"data row206 col3\" >1935991</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col4\" class=\"data row206 col4\" >-66186</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row206_col5\" class=\"data row206 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row207\" class=\"row_heading level0 row207\" >207</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col0\" class=\"data row207 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col1\" class=\"data row207 col1\" >3</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col2\" class=\"data row207 col2\" >2010648</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col3\" class=\"data row207 col3\" >1957483</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col4\" class=\"data row207 col4\" >-53165</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row207_col5\" class=\"data row207 col5\" >-2.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row208\" class=\"row_heading level0 row208\" >208</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col0\" class=\"data row208 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col1\" class=\"data row208 col1\" >4</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col2\" class=\"data row208 col2\" >1993239</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col3\" class=\"data row208 col3\" >1961199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col4\" class=\"data row208 col4\" >-32040</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row208_col5\" class=\"data row208 col5\" >-1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row209\" class=\"row_heading level0 row209\" >209</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col0\" class=\"data row209 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col1\" class=\"data row209 col1\" >5</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col2\" class=\"data row209 col2\" >1988080</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col3\" class=\"data row209 col3\" >1962561</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col4\" class=\"data row209 col4\" >-25519</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row209_col5\" class=\"data row209 col5\" >-1.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row210\" class=\"row_heading level0 row210\" >210</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col0\" class=\"data row210 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col1\" class=\"data row210 col1\" >6</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col2\" class=\"data row210 col2\" >1993603</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col3\" class=\"data row210 col3\" >2024870</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col4\" class=\"data row210 col4\" >31267</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row210_col5\" class=\"data row210 col5\" >1.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row211\" class=\"row_heading level0 row211\" >211</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col0\" class=\"data row211 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col1\" class=\"data row211 col1\" >7</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col2\" class=\"data row211 col2\" >1979907</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col3\" class=\"data row211 col3\" >2032494</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col4\" class=\"data row211 col4\" >52587</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row211_col5\" class=\"data row211 col5\" >2.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row212\" class=\"row_heading level0 row212\" >212</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col0\" class=\"data row212 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col1\" class=\"data row212 col1\" >8</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col2\" class=\"data row212 col2\" >1971142</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col3\" class=\"data row212 col3\" >2015285</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col4\" class=\"data row212 col4\" >44143</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row212_col5\" class=\"data row212 col5\" >2.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row213\" class=\"row_heading level0 row213\" >213</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col0\" class=\"data row213 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col1\" class=\"data row213 col1\" >9</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col2\" class=\"data row213 col2\" >2018378</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col3\" class=\"data row213 col3\" >2010659</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col4\" class=\"data row213 col4\" >-7719</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row213_col5\" class=\"data row213 col5\" >-0.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row214\" class=\"row_heading level0 row214\" >214</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col0\" class=\"data row214 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col1\" class=\"data row214 col1\" >10</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col2\" class=\"data row214 col2\" >2044895</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col3\" class=\"data row214 col3\" >2016680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col4\" class=\"data row214 col4\" >-28215</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row214_col5\" class=\"data row214 col5\" >-1.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row215\" class=\"row_heading level0 row215\" >215</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col0\" class=\"data row215 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col1\" class=\"data row215 col1\" >11</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col2\" class=\"data row215 col2\" >2010714</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col3\" class=\"data row215 col3\" >2003233</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col4\" class=\"data row215 col4\" >-7481</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row215_col5\" class=\"data row215 col5\" >-0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row216\" class=\"row_heading level0 row216\" >216</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col0\" class=\"data row216 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col1\" class=\"data row216 col1\" >12</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col2\" class=\"data row216 col2\" >2009630</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col3\" class=\"data row216 col3\" >1994846</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col4\" class=\"data row216 col4\" >-14784</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row216_col5\" class=\"data row216 col5\" >-0.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row217\" class=\"row_heading level0 row217\" >217</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col0\" class=\"data row217 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col1\" class=\"data row217 col1\" >13</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col2\" class=\"data row217 col2\" >2014717</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col3\" class=\"data row217 col3\" >2042116</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col4\" class=\"data row217 col4\" >27399</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row217_col5\" class=\"data row217 col5\" >1.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row218\" class=\"row_heading level0 row218\" >218</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col0\" class=\"data row218 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col1\" class=\"data row218 col1\" >14</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col2\" class=\"data row218 col2\" >2022701</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col3\" class=\"data row218 col3\" >2068915</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col4\" class=\"data row218 col4\" >46214</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row218_col5\" class=\"data row218 col5\" >2.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row219\" class=\"row_heading level0 row219\" >219</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col0\" class=\"data row219 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col1\" class=\"data row219 col1\" >15</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col2\" class=\"data row219 col2\" >2060560</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col3\" class=\"data row219 col3\" >2035734</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col4\" class=\"data row219 col4\" >-24826</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row219_col5\" class=\"data row219 col5\" >-1.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row220\" class=\"row_heading level0 row220\" >220</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col0\" class=\"data row220 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col1\" class=\"data row220 col1\" >16</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col2\" class=\"data row220 col2\" >2098220</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col3\" class=\"data row220 col3\" >2037134</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col4\" class=\"data row220 col4\" >-61086</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row220_col5\" class=\"data row220 col5\" >-2.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row221\" class=\"row_heading level0 row221\" >221</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col0\" class=\"data row221 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col1\" class=\"data row221 col1\" >17</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col2\" class=\"data row221 col2\" >2123529</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col3\" class=\"data row221 col3\" >2047152</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col4\" class=\"data row221 col4\" >-76377</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row221_col5\" class=\"data row221 col5\" >-3.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row222\" class=\"row_heading level0 row222\" >222</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col0\" class=\"data row222 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col1\" class=\"data row222 col1\" >18</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col2\" class=\"data row222 col2\" >2185272</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col3\" class=\"data row222 col3\" >2062176</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col4\" class=\"data row222 col4\" >-123096</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row222_col5\" class=\"data row222 col5\" >-5.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row223\" class=\"row_heading level0 row223\" >223</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col0\" class=\"data row223 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col1\" class=\"data row223 col1\" >19</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col2\" class=\"data row223 col2\" >2236505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col3\" class=\"data row223 col3\" >2107128</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col4\" class=\"data row223 col4\" >-129377</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row223_col5\" class=\"data row223 col5\" >-5.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row224\" class=\"row_heading level0 row224\" >224</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col0\" class=\"data row224 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col1\" class=\"data row224 col1\" >20</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col2\" class=\"data row224 col2\" >2236672</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col3\" class=\"data row224 col3\" >2150114</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col4\" class=\"data row224 col4\" >-86558</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row224_col5\" class=\"data row224 col5\" >-3.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row225\" class=\"row_heading level0 row225\" >225</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col0\" class=\"data row225 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col1\" class=\"data row225 col1\" >21</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col2\" class=\"data row225 col2\" >2146873</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col3\" class=\"data row225 col3\" >2179456</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col4\" class=\"data row225 col4\" >32583</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row225_col5\" class=\"data row225 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row226\" class=\"row_heading level0 row226\" >226</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col0\" class=\"data row226 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col1\" class=\"data row226 col1\" >22</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col2\" class=\"data row226 col2\" >2098806</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col3\" class=\"data row226 col3\" >2245270</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col4\" class=\"data row226 col4\" >146464</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row226_col5\" class=\"data row226 col5\" >6.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row227\" class=\"row_heading level0 row227\" >227</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col0\" class=\"data row227 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col1\" class=\"data row227 col1\" >23</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col2\" class=\"data row227 col2\" >2066160</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col3\" class=\"data row227 col3\" >2299862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col4\" class=\"data row227 col4\" >233702</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row227_col5\" class=\"data row227 col5\" >11.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row228\" class=\"row_heading level0 row228\" >228</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col0\" class=\"data row228 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col1\" class=\"data row228 col1\" >24</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col2\" class=\"data row228 col2\" >2082255</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col3\" class=\"data row228 col3\" >2302374</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col4\" class=\"data row228 col4\" >220119</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row228_col5\" class=\"data row228 col5\" >10.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row229\" class=\"row_heading level0 row229\" >229</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col0\" class=\"data row229 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col1\" class=\"data row229 col1\" >25</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col2\" class=\"data row229 col2\" >2112297</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col3\" class=\"data row229 col3\" >2214495</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col4\" class=\"data row229 col4\" >102198</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row229_col5\" class=\"data row229 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row230\" class=\"row_heading level0 row230\" >230</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col0\" class=\"data row230 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col1\" class=\"data row230 col1\" >26</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col2\" class=\"data row230 col2\" >2058475</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col3\" class=\"data row230 col3\" >2167162</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col4\" class=\"data row230 col4\" >108687</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row230_col5\" class=\"data row230 col5\" >5.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row231\" class=\"row_heading level0 row231\" >231</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col0\" class=\"data row231 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col1\" class=\"data row231 col1\" >27</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col2\" class=\"data row231 col2\" >2101848</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col3\" class=\"data row231 col3\" >2133288</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col4\" class=\"data row231 col4\" >31440</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row231_col5\" class=\"data row231 col5\" >1.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row232\" class=\"row_heading level0 row232\" >232</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col0\" class=\"data row232 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col1\" class=\"data row232 col1\" >28</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col2\" class=\"data row232 col2\" >2112560</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col3\" class=\"data row232 col3\" >2146491</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col4\" class=\"data row232 col4\" >33931</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row232_col5\" class=\"data row232 col5\" >1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row233\" class=\"row_heading level0 row233\" >233</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col0\" class=\"data row233 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col1\" class=\"data row233 col1\" >29</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col2\" class=\"data row233 col2\" >2097973</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col3\" class=\"data row233 col3\" >2171916</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col4\" class=\"data row233 col4\" >73943</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row233_col5\" class=\"data row233 col5\" >3.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row234\" class=\"row_heading level0 row234\" >234</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col0\" class=\"data row234 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col1\" class=\"data row234 col1\" >30</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col2\" class=\"data row234 col2\" >2136744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col3\" class=\"data row234 col3\" >2113094</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col4\" class=\"data row234 col4\" >-23650</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row234_col5\" class=\"data row234 col5\" >-1.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row235\" class=\"row_heading level0 row235\" >235</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col0\" class=\"data row235 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col1\" class=\"data row235 col1\" >31</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col2\" class=\"data row235 col2\" >2016077</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col3\" class=\"data row235 col3\" >2151378</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col4\" class=\"data row235 col4\" >135301</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row235_col5\" class=\"data row235 col5\" >6.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row236\" class=\"row_heading level0 row236\" >236</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col0\" class=\"data row236 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col1\" class=\"data row236 col1\" >32</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col2\" class=\"data row236 col2\" >1981455</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col3\" class=\"data row236 col3\" >2156394</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col4\" class=\"data row236 col4\" >174939</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row236_col5\" class=\"data row236 col5\" >8.83%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row237\" class=\"row_heading level0 row237\" >237</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col0\" class=\"data row237 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col1\" class=\"data row237 col1\" >33</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col2\" class=\"data row237 col2\" >1969936</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col3\" class=\"data row237 col3\" >2137112</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col4\" class=\"data row237 col4\" >167176</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row237_col5\" class=\"data row237 col5\" >8.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row238\" class=\"row_heading level0 row238\" >238</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col0\" class=\"data row238 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col1\" class=\"data row238 col1\" >34</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col2\" class=\"data row238 col2\" >1913458</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col3\" class=\"data row238 col3\" >2171871</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col4\" class=\"data row238 col4\" >258413</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row238_col5\" class=\"data row238 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row239\" class=\"row_heading level0 row239\" >239</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col0\" class=\"data row239 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col1\" class=\"data row239 col1\" >35</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col2\" class=\"data row239 col2\" >1973699</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col3\" class=\"data row239 col3\" >2047905</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col4\" class=\"data row239 col4\" >74206</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row239_col5\" class=\"data row239 col5\" >3.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row240\" class=\"row_heading level0 row240\" >240</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col0\" class=\"data row240 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col1\" class=\"data row240 col1\" >36</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col2\" class=\"data row240 col2\" >1922791</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col3\" class=\"data row240 col3\" >2010831</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col4\" class=\"data row240 col4\" >88040</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row240_col5\" class=\"data row240 col5\" >4.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row241\" class=\"row_heading level0 row241\" >241</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col0\" class=\"data row241 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col1\" class=\"data row241 col1\" >37</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col2\" class=\"data row241 col2\" >1962229</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col3\" class=\"data row241 col3\" >1996862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col4\" class=\"data row241 col4\" >34633</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row241_col5\" class=\"data row241 col5\" >1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row242\" class=\"row_heading level0 row242\" >242</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col0\" class=\"data row242 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col1\" class=\"data row242 col1\" >38</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col2\" class=\"data row242 col2\" >2052176</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col3\" class=\"data row242 col3\" >1938503</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col4\" class=\"data row242 col4\" >-113673</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row242_col5\" class=\"data row242 col5\" >-5.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row243\" class=\"row_heading level0 row243\" >243</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col0\" class=\"data row243 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col1\" class=\"data row243 col1\" >39</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col2\" class=\"data row243 col2\" >2175745</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col3\" class=\"data row243 col3\" >1995795</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col4\" class=\"data row243 col4\" >-179950</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row243_col5\" class=\"data row243 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row244\" class=\"row_heading level0 row244\" >244</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col0\" class=\"data row244 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col1\" class=\"data row244 col1\" >40</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col2\" class=\"data row244 col2\" >2197964</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col3\" class=\"data row244 col3\" >1942194</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col4\" class=\"data row244 col4\" >-255770</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row244_col5\" class=\"data row244 col5\" >-11.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row245\" class=\"row_heading level0 row245\" >245</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col0\" class=\"data row245 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col1\" class=\"data row245 col1\" >41</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col2\" class=\"data row245 col2\" >2089576</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col3\" class=\"data row245 col3\" >1978607</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col4\" class=\"data row245 col4\" >-110969</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row245_col5\" class=\"data row245 col5\" >-5.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row246\" class=\"row_heading level0 row246\" >246</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col0\" class=\"data row246 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col1\" class=\"data row246 col1\" >42</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col2\" class=\"data row246 col2\" >2050930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col3\" class=\"data row246 col3\" >2065491</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col4\" class=\"data row246 col4\" >14561</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row246_col5\" class=\"data row246 col5\" >0.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row247\" class=\"row_heading level0 row247\" >247</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col0\" class=\"data row247 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col1\" class=\"data row247 col1\" >43</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col2\" class=\"data row247 col2\" >2062862</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col3\" class=\"data row247 col3\" >2185890</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col4\" class=\"data row247 col4\" >123028</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row247_col5\" class=\"data row247 col5\" >5.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row248\" class=\"row_heading level0 row248\" >248</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col0\" class=\"data row248 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col1\" class=\"data row248 col1\" >44</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col2\" class=\"data row248 col2\" >2103936</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col3\" class=\"data row248 col3\" >2205835</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col4\" class=\"data row248 col4\" >101899</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row248_col5\" class=\"data row248 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row249\" class=\"row_heading level0 row249\" >249</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col0\" class=\"data row249 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col1\" class=\"data row249 col1\" >45</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col2\" class=\"data row249 col2\" >2236654</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col3\" class=\"data row249 col3\" >2095203</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col4\" class=\"data row249 col4\" >-141451</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row249_col5\" class=\"data row249 col5\" >-6.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row250\" class=\"row_heading level0 row250\" >250</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col0\" class=\"data row250 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col1\" class=\"data row250 col1\" >46</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col2\" class=\"data row250 col2\" >2290942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col3\" class=\"data row250 col3\" >2054118</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col4\" class=\"data row250 col4\" >-236824</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row250_col5\" class=\"data row250 col5\" >-10.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row251\" class=\"row_heading level0 row251\" >251</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col0\" class=\"data row251 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col1\" class=\"data row251 col1\" >47</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col2\" class=\"data row251 col2\" >2297533</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col3\" class=\"data row251 col3\" >2063366</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col4\" class=\"data row251 col4\" >-234167</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row251_col5\" class=\"data row251 col5\" >-10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row252\" class=\"row_heading level0 row252\" >252</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col0\" class=\"data row252 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col1\" class=\"data row252 col1\" >48</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col2\" class=\"data row252 col2\" >2299367</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col3\" class=\"data row252 col3\" >2101346</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col4\" class=\"data row252 col4\" >-198021</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row252_col5\" class=\"data row252 col5\" >-8.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row253\" class=\"row_heading level0 row253\" >253</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col0\" class=\"data row253 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col1\" class=\"data row253 col1\" >49</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col2\" class=\"data row253 col2\" >2336640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col3\" class=\"data row253 col3\" >2230032</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col4\" class=\"data row253 col4\" >-106608</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row253_col5\" class=\"data row253 col5\" >-4.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row254\" class=\"row_heading level0 row254\" >254</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col0\" class=\"data row254 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col1\" class=\"data row254 col1\" >50</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col2\" class=\"data row254 col2\" >2355369</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col3\" class=\"data row254 col3\" >2280640</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col4\" class=\"data row254 col4\" >-74729</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row254_col5\" class=\"data row254 col5\" >-3.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row255\" class=\"row_heading level0 row255\" >255</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col0\" class=\"data row255 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col1\" class=\"data row255 col1\" >51</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col2\" class=\"data row255 col2\" >2289194</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col3\" class=\"data row255 col3\" >2283994</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col4\" class=\"data row255 col4\" >-5200</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row255_col5\" class=\"data row255 col5\" >-0.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row256\" class=\"row_heading level0 row256\" >256</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col0\" class=\"data row256 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col1\" class=\"data row256 col1\" >52</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col2\" class=\"data row256 col2\" >2283423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col3\" class=\"data row256 col3\" >2282387</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col4\" class=\"data row256 col4\" >-1036</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row256_col5\" class=\"data row256 col5\" >-0.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row257\" class=\"row_heading level0 row257\" >257</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col0\" class=\"data row257 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col1\" class=\"data row257 col1\" >53</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col2\" class=\"data row257 col2\" >2268480</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col3\" class=\"data row257 col3\" >2316102</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col4\" class=\"data row257 col4\" >47622</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row257_col5\" class=\"data row257 col5\" >2.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row258\" class=\"row_heading level0 row258\" >258</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col0\" class=\"data row258 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col1\" class=\"data row258 col1\" >54</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col2\" class=\"data row258 col2\" >2196807</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col3\" class=\"data row258 col3\" >2332003</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col4\" class=\"data row258 col4\" >135196</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row258_col5\" class=\"data row258 col5\" >6.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row259\" class=\"row_heading level0 row259\" >259</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col0\" class=\"data row259 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col1\" class=\"data row259 col1\" >55</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col2\" class=\"data row259 col2\" >2183771</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col3\" class=\"data row259 col3\" >2263429</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col4\" class=\"data row259 col4\" >79658</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row259_col5\" class=\"data row259 col5\" >3.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row260\" class=\"row_heading level0 row260\" >260</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col0\" class=\"data row260 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col1\" class=\"data row260 col1\" >56</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col2\" class=\"data row260 col2\" >2108684</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col3\" class=\"data row260 col3\" >2255009</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col4\" class=\"data row260 col4\" >146325</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row260_col5\" class=\"data row260 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row261\" class=\"row_heading level0 row261\" >261</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col0\" class=\"data row261 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col1\" class=\"data row261 col1\" >57</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col2\" class=\"data row261 col2\" >2036521</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col3\" class=\"data row261 col3\" >2237219</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col4\" class=\"data row261 col4\" >200698</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row261_col5\" class=\"data row261 col5\" >9.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row262\" class=\"row_heading level0 row262\" >262</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col0\" class=\"data row262 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col1\" class=\"data row262 col1\" >58</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col2\" class=\"data row262 col2\" >1963767</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col3\" class=\"data row262 col3\" >2163908</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col4\" class=\"data row262 col4\" >200141</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row262_col5\" class=\"data row262 col5\" >10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row263\" class=\"row_heading level0 row263\" >263</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col0\" class=\"data row263 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col1\" class=\"data row263 col1\" >59</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col2\" class=\"data row263 col2\" >1914774</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col3\" class=\"data row263 col3\" >2148934</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col4\" class=\"data row263 col4\" >234160</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row263_col5\" class=\"data row263 col5\" >12.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row264\" class=\"row_heading level0 row264\" >264</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col0\" class=\"data row264 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col1\" class=\"data row264 col1\" >60</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col2\" class=\"data row264 col2\" >1874501</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col3\" class=\"data row264 col3\" >2071869</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col4\" class=\"data row264 col4\" >197368</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row264_col5\" class=\"data row264 col5\" >10.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row265\" class=\"row_heading level0 row265\" >265</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col0\" class=\"data row265 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col1\" class=\"data row265 col1\" >61</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col2\" class=\"data row265 col2\" >1828708</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col3\" class=\"data row265 col3\" >1997711</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col4\" class=\"data row265 col4\" >169003</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row265_col5\" class=\"data row265 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row266\" class=\"row_heading level0 row266\" >266</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col0\" class=\"data row266 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col1\" class=\"data row266 col1\" >62</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col2\" class=\"data row266 col2\" >1815999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col3\" class=\"data row266 col3\" >1922402</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col4\" class=\"data row266 col4\" >106403</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row266_col5\" class=\"data row266 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row267\" class=\"row_heading level0 row267\" >267</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col0\" class=\"data row267 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col1\" class=\"data row267 col1\" >63</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col2\" class=\"data row267 col2\" >1898264</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col3\" class=\"data row267 col3\" >1870596</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col4\" class=\"data row267 col4\" >-27668</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row267_col5\" class=\"data row267 col5\" >-1.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row268\" class=\"row_heading level0 row268\" >268</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col0\" class=\"data row268 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col1\" class=\"data row268 col1\" >64</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col2\" class=\"data row268 col2\" >1414222</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col3\" class=\"data row268 col3\" >1826744</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col4\" class=\"data row268 col4\" >412522</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row268_col5\" class=\"data row268 col5\" >29.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row269\" class=\"row_heading level0 row269\" >269</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col0\" class=\"data row269 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col1\" class=\"data row269 col1\" >65</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col2\" class=\"data row269 col2\" >1405839</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col3\" class=\"data row269 col3\" >1776052</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col4\" class=\"data row269 col4\" >370213</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row269_col5\" class=\"data row269 col5\" >26.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row270\" class=\"row_heading level0 row270\" >270</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col0\" class=\"data row270 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col1\" class=\"data row270 col1\" >66</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col2\" class=\"data row270 col2\" >1381541</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col3\" class=\"data row270 col3\" >1758337</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col4\" class=\"data row270 col4\" >376796</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row270_col5\" class=\"data row270 col5\" >27.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row271\" class=\"row_heading level0 row271\" >271</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col0\" class=\"data row271 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col1\" class=\"data row271 col1\" >67</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col2\" class=\"data row271 col2\" >1423562</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col3\" class=\"data row271 col3\" >1832243</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col4\" class=\"data row271 col4\" >408681</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row271_col5\" class=\"data row271 col5\" >28.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row272\" class=\"row_heading level0 row272\" >272</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col0\" class=\"data row272 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col1\" class=\"data row272 col1\" >68</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col2\" class=\"data row272 col2\" >1254117</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col3\" class=\"data row272 col3\" >1361081</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col4\" class=\"data row272 col4\" >106964</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row272_col5\" class=\"data row272 col5\" >8.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row273\" class=\"row_heading level0 row273\" >273</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col0\" class=\"data row273 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col1\" class=\"data row273 col1\" >69</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col2\" class=\"data row273 col2\" >1161048</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col3\" class=\"data row273 col3\" >1347423</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col4\" class=\"data row273 col4\" >186375</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row273_col5\" class=\"data row273 col5\" >16.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row274\" class=\"row_heading level0 row274\" >274</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col0\" class=\"data row274 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col1\" class=\"data row274 col1\" >70</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col2\" class=\"data row274 col2\" >1108504</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col3\" class=\"data row274 col3\" >1316930</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col4\" class=\"data row274 col4\" >208426</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row274_col5\" class=\"data row274 col5\" >18.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row275\" class=\"row_heading level0 row275\" >275</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col0\" class=\"data row275 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col1\" class=\"data row275 col1\" >71</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col2\" class=\"data row275 col2\" >1050349</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col3\" class=\"data row275 col3\" >1350590</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col4\" class=\"data row275 col4\" >300241</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row275_col5\" class=\"data row275 col5\" >28.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row276\" class=\"row_heading level0 row276\" >276</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col0\" class=\"data row276 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col1\" class=\"data row276 col1\" >72</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col2\" class=\"data row276 col2\" >1021291</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col3\" class=\"data row276 col3\" >1183363</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col4\" class=\"data row276 col4\" >162072</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row276_col5\" class=\"data row276 col5\" >15.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row277\" class=\"row_heading level0 row277\" >277</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col0\" class=\"data row277 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col1\" class=\"data row277 col1\" >73</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col2\" class=\"data row277 col2\" >955658</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col3\" class=\"data row277 col3\" >1089027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col4\" class=\"data row277 col4\" >133369</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row277_col5\" class=\"data row277 col5\" >13.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row278\" class=\"row_heading level0 row278\" >278</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col0\" class=\"data row278 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col1\" class=\"data row278 col1\" >74</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col2\" class=\"data row278 col2\" >927165</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col3\" class=\"data row278 col3\" >1032543</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col4\" class=\"data row278 col4\" >105378</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row278_col5\" class=\"data row278 col5\" >11.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row279\" class=\"row_heading level0 row279\" >279</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col0\" class=\"data row279 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col1\" class=\"data row279 col1\" >75</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col2\" class=\"data row279 col2\" >906215</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col3\" class=\"data row279 col3\" >970796</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col4\" class=\"data row279 col4\" >64581</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row279_col5\" class=\"data row279 col5\" >7.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row280\" class=\"row_heading level0 row280\" >280</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col0\" class=\"data row280 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col1\" class=\"data row280 col1\" >76</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col2\" class=\"data row280 col2\" >828129</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col3\" class=\"data row280 col3\" >935833</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col4\" class=\"data row280 col4\" >107704</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row280_col5\" class=\"data row280 col5\" >13.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row281\" class=\"row_heading level0 row281\" >281</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col0\" class=\"data row281 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col1\" class=\"data row281 col1\" >77</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col2\" class=\"data row281 col2\" >818306</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col3\" class=\"data row281 col3\" >866942</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col4\" class=\"data row281 col4\" >48636</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row281_col5\" class=\"data row281 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row282\" class=\"row_heading level0 row282\" >282</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col0\" class=\"data row282 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col1\" class=\"data row282 col1\" >78</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col2\" class=\"data row282 col2\" >799408</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col3\" class=\"data row282 col3\" >831915</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col4\" class=\"data row282 col4\" >32507</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row282_col5\" class=\"data row282 col5\" >4.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row283\" class=\"row_heading level0 row283\" >283</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col0\" class=\"data row283 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col1\" class=\"data row283 col1\" >79</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col2\" class=\"data row283 col2\" >781027</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col3\" class=\"data row283 col3\" >803078</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col4\" class=\"data row283 col4\" >22051</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row283_col5\" class=\"data row283 col5\" >2.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row284\" class=\"row_heading level0 row284\" >284</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col0\" class=\"data row284 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col1\" class=\"data row284 col1\" >80</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col2\" class=\"data row284 col2\" >770509</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col3\" class=\"data row284 col3\" >723310</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col4\" class=\"data row284 col4\" >-47199</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row284_col5\" class=\"data row284 col5\" >-6.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row285\" class=\"row_heading level0 row285\" >285</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col0\" class=\"data row285 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col1\" class=\"data row285 col1\" >81</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col2\" class=\"data row285 col2\" >716533</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col3\" class=\"data row285 col3\" >704052</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col4\" class=\"data row285 col4\" >-12481</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row285_col5\" class=\"data row285 col5\" >-1.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row286\" class=\"row_heading level0 row286\" >286</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col0\" class=\"data row286 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col1\" class=\"data row286 col1\" >82</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col2\" class=\"data row286 col2\" >695544</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col3\" class=\"data row286 col3\" >675643</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col4\" class=\"data row286 col4\" >-19901</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row286_col5\" class=\"data row286 col5\" >-2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row287\" class=\"row_heading level0 row287\" >287</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col0\" class=\"data row287 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col1\" class=\"data row287 col1\" >83</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col2\" class=\"data row287 col2\" >658441</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col3\" class=\"data row287 col3\" >647071</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col4\" class=\"data row287 col4\" >-11370</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row287_col5\" class=\"data row287 col5\" >-1.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row288\" class=\"row_heading level0 row288\" >288</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col0\" class=\"data row288 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col1\" class=\"data row288 col1\" >84</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col2\" class=\"data row288 col2\" >611338</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col3\" class=\"data row288 col3\" >623984</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col4\" class=\"data row288 col4\" >12646</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row288_col5\" class=\"data row288 col5\" >2.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row289\" class=\"row_heading level0 row289\" >289</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col0\" class=\"data row289 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col1\" class=\"data row289 col1\" >85</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col2\" class=\"data row289 col2\" >577352</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col3\" class=\"data row289 col3\" >564605</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col4\" class=\"data row289 col4\" >-12747</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row289_col5\" class=\"data row289 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row290\" class=\"row_heading level0 row290\" >290</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col0\" class=\"data row290 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col1\" class=\"data row290 col1\" >86</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col2\" class=\"data row290 col2\" >526153</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col3\" class=\"data row290 col3\" >531680</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col4\" class=\"data row290 col4\" >5527</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row290_col5\" class=\"data row290 col5\" >1.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row291\" class=\"row_heading level0 row291\" >291</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col0\" class=\"data row291 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col1\" class=\"data row291 col1\" >87</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col2\" class=\"data row291 col2\" >467575</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col3\" class=\"data row291 col3\" >486253</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col4\" class=\"data row291 col4\" >18678</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row291_col5\" class=\"data row291 col5\" >3.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row292\" class=\"row_heading level0 row292\" >292</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col0\" class=\"data row292 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col1\" class=\"data row292 col1\" >88</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col2\" class=\"data row292 col2\" >420437</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col3\" class=\"data row292 col3\" >433947</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col4\" class=\"data row292 col4\" >13510</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row292_col5\" class=\"data row292 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row293\" class=\"row_heading level0 row293\" >293</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col0\" class=\"data row293 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col1\" class=\"data row293 col1\" >89</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col2\" class=\"data row293 col2\" >365732</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col3\" class=\"data row293 col3\" >392978</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col4\" class=\"data row293 col4\" >27246</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row293_col5\" class=\"data row293 col5\" >7.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row294\" class=\"row_heading level0 row294\" >294</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col0\" class=\"data row294 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col1\" class=\"data row294 col1\" >90</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col2\" class=\"data row294 col2\" >306925</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col3\" class=\"data row294 col3\" >341430</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col4\" class=\"data row294 col4\" >34505</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row294_col5\" class=\"data row294 col5\" >11.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row295\" class=\"row_heading level0 row295\" >295</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col0\" class=\"data row295 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col1\" class=\"data row295 col1\" >91</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col2\" class=\"data row295 col2\" >240151</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col3\" class=\"data row295 col3\" >287889</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col4\" class=\"data row295 col4\" >47738</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row295_col5\" class=\"data row295 col5\" >19.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row296\" class=\"row_heading level0 row296\" >296</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col0\" class=\"data row296 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col1\" class=\"data row296 col1\" >92</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col2\" class=\"data row296 col2\" >205379</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col3\" class=\"data row296 col3\" >243648</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col4\" class=\"data row296 col4\" >38269</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row296_col5\" class=\"data row296 col5\" >18.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row297\" class=\"row_heading level0 row297\" >297</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col0\" class=\"data row297 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col1\" class=\"data row297 col1\" >93</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col2\" class=\"data row297 col2\" >158882</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col3\" class=\"data row297 col3\" >199426</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col4\" class=\"data row297 col4\" >40544</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row297_col5\" class=\"data row297 col5\" >25.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row298\" class=\"row_heading level0 row298\" >298</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col0\" class=\"data row298 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col1\" class=\"data row298 col1\" >94</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col2\" class=\"data row298 col2\" >126948</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col3\" class=\"data row298 col3\" >155637</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col4\" class=\"data row298 col4\" >28689</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row298_col5\" class=\"data row298 col5\" >22.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row299\" class=\"row_heading level0 row299\" >299</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col0\" class=\"data row299 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col1\" class=\"data row299 col1\" >95</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col2\" class=\"data row299 col2\" >99341</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col3\" class=\"data row299 col3\" >113732</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col4\" class=\"data row299 col4\" >14391</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row299_col5\" class=\"data row299 col5\" >14.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row300\" class=\"row_heading level0 row300\" >300</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col0\" class=\"data row300 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col1\" class=\"data row300 col1\" >96</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col2\" class=\"data row300 col2\" >75139</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col3\" class=\"data row300 col3\" >89432</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col4\" class=\"data row300 col4\" >14293</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row300_col5\" class=\"data row300 col5\" >19.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row301\" class=\"row_heading level0 row301\" >301</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col0\" class=\"data row301 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col1\" class=\"data row301 col1\" >97</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col2\" class=\"data row301 col2\" >54118</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col3\" class=\"data row301 col3\" >62779</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col4\" class=\"data row301 col4\" >8661</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row301_col5\" class=\"data row301 col5\" >16.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row302\" class=\"row_heading level0 row302\" >302</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col0\" class=\"data row302 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col1\" class=\"data row302 col1\" >98</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col2\" class=\"data row302 col2\" >37532</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col3\" class=\"data row302 col3\" >46208</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col4\" class=\"data row302 col4\" >8676</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row302_col5\" class=\"data row302 col5\" >23.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row303\" class=\"row_heading level0 row303\" >303</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col0\" class=\"data row303 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col1\" class=\"data row303 col1\" >99</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col2\" class=\"data row303 col2\" >26074</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col3\" class=\"data row303 col3\" >32517</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col4\" class=\"data row303 col4\" >6443</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row303_col5\" class=\"data row303 col5\" >24.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row304\" class=\"row_heading level0 row304\" >304</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col0\" class=\"data row304 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col1\" class=\"data row304 col1\" >100</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col2\" class=\"data row304 col2\" >45058</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col3\" class=\"data row304 col3\" >58008</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col4\" class=\"data row304 col4\" >12950</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row304_col5\" class=\"data row304 col5\" >28.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122level0_row305\" class=\"row_heading level0 row305\" >305</th>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col0\" class=\"data row305 col0\" >2</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col1\" class=\"data row305 col1\" >999</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col2\" class=\"data row305 col2\" >157258820</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col3\" class=\"data row305 col3\" >161952064</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col4\" class=\"data row305 col4\" >4693244</td>\n",
+       "                        <td id=\"T_3d06be7a_5280_11eb_8c0f_acde48001122row305_col5\" class=\"data row305 col5\" >2.98%</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd9c2be5e50>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "change = us_pop['2014'] - us_pop['2010']\n",
+    "\n",
+    "\n",
+    "census = us_pop\n",
+    "\n",
+    "census['Change'] = change\n",
+    "\n",
+    "census['Percent Change'] = change/us_pop['2010']\n",
+    "\n",
+    "census.style.format({'Percent Change': \"{:,.2%}\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Sorting the data.** Let us sort the table in decreasing order of the absolute change in population."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_3daade6a_5280_11eb_8c0f_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >SEX</th>        <th class=\"col_heading level0 col1\" >AGE</th>        <th class=\"col_heading level0 col2\" >2010</th>        <th class=\"col_heading level0 col3\" >2014</th>        <th class=\"col_heading level0 col4\" >Change</th>        <th class=\"col_heading level0 col5\" >Percent Change</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row0\" class=\"row_heading level0 row0\" >101</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col0\" class=\"data row0 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col1\" class=\"data row0 col1\" >999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col2\" class=\"data row0 col2\" >309346863</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col3\" class=\"data row0 col3\" >318907401</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col4\" class=\"data row0 col4\" >9560538</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row0_col5\" class=\"data row0 col5\" >3.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row1\" class=\"row_heading level0 row1\" >203</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col0\" class=\"data row1 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col1\" class=\"data row1 col1\" >999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col2\" class=\"data row1 col2\" >152088043</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col3\" class=\"data row1 col3\" >156955337</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col4\" class=\"data row1 col4\" >4867294</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row1_col5\" class=\"data row1 col5\" >3.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row2\" class=\"row_heading level0 row2\" >305</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col0\" class=\"data row2 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col1\" class=\"data row2 col1\" >999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col2\" class=\"data row2 col2\" >157258820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col3\" class=\"data row2 col3\" >161952064</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col4\" class=\"data row2 col4\" >4693244</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row2_col5\" class=\"data row2 col5\" >2.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row3\" class=\"row_heading level0 row3\" >67</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col0\" class=\"data row3 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col1\" class=\"data row3 col1\" >67</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col2\" class=\"data row3 col2\" >2693707</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col3\" class=\"data row3 col3\" >3485241</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col4\" class=\"data row3 col4\" >791534</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row3_col5\" class=\"data row3 col5\" >29.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row4\" class=\"row_heading level0 row4\" >64</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col0\" class=\"data row4 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col1\" class=\"data row4 col1\" >64</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col2\" class=\"data row4 col2\" >2706055</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col3\" class=\"data row4 col3\" >3487559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col4\" class=\"data row4 col4\" >781504</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row4_col5\" class=\"data row4 col5\" >28.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row5\" class=\"row_heading level0 row5\" >66</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col0\" class=\"data row5 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col1\" class=\"data row5 col1\" >66</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col2\" class=\"data row5 col2\" >2621335</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col3\" class=\"data row5 col3\" >3347060</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col4\" class=\"data row5 col4\" >725725</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row5_col5\" class=\"data row5 col5\" >27.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row6\" class=\"row_heading level0 row6\" >65</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col0\" class=\"data row6 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col1\" class=\"data row6 col1\" >65</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col2\" class=\"data row6 col2\" >2678525</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col3\" class=\"data row6 col3\" >3382824</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col4\" class=\"data row6 col4\" >704299</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row6_col5\" class=\"data row6 col5\" >26.29%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row7\" class=\"row_heading level0 row7\" >71</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col0\" class=\"data row7 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col1\" class=\"data row7 col1\" >71</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col2\" class=\"data row7 col2\" >1953607</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col3\" class=\"data row7 col3\" >2519705</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col4\" class=\"data row7 col4\" >566098</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row7_col5\" class=\"data row7 col5\" >28.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row8\" class=\"row_heading level0 row8\" >34</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col0\" class=\"data row8 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col1\" class=\"data row8 col1\" >34</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col2\" class=\"data row8 col2\" >3822189</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col3\" class=\"data row8 col3\" >4364748</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col4\" class=\"data row8 col4\" >542559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row8_col5\" class=\"data row8 col5\" >14.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row9\" class=\"row_heading level0 row9\" >23</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col0\" class=\"data row9 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col1\" class=\"data row9 col1\" >23</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col2\" class=\"data row9 col2\" >4217228</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col3\" class=\"data row9 col3\" >4702156</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col4\" class=\"data row9 col4\" >484928</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row9_col5\" class=\"data row9 col5\" >11.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row10\" class=\"row_heading level0 row10\" >59</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col0\" class=\"data row10 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col1\" class=\"data row10 col1\" >59</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col2\" class=\"data row10 col2\" >3694254</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col3\" class=\"data row10 col3\" >4155521</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col4\" class=\"data row10 col4\" >461267</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row10_col5\" class=\"data row10 col5\" >12.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row11\" class=\"row_heading level0 row11\" >24</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col0\" class=\"data row11 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col1\" class=\"data row11 col1\" >24</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col2\" class=\"data row11 col2\" >4243602</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col3\" class=\"data row11 col3\" >4695411</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col4\" class=\"data row11 col4\" >451809</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row11_col5\" class=\"data row11 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row12\" class=\"row_heading level0 row12\" >268</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col0\" class=\"data row12 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col1\" class=\"data row12 col1\" >64</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col2\" class=\"data row12 col2\" >1414222</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col3\" class=\"data row12 col3\" >1826744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col4\" class=\"data row12 col4\" >412522</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row12_col5\" class=\"data row12 col5\" >29.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row13\" class=\"row_heading level0 row13\" >271</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col0\" class=\"data row13 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col1\" class=\"data row13 col1\" >67</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col2\" class=\"data row13 col2\" >1423562</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col3\" class=\"data row13 col3\" >1832243</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col4\" class=\"data row13 col4\" >408681</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row13_col5\" class=\"data row13 col5\" >28.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row14\" class=\"row_heading level0 row14\" >70</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col0\" class=\"data row14 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col1\" class=\"data row14 col1\" >70</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col2\" class=\"data row14 col2\" >2062577</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col3\" class=\"data row14 col3\" >2465438</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col4\" class=\"data row14 col4\" >402861</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row14_col5\" class=\"data row14 col5\" >19.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row15\" class=\"row_heading level0 row15\" >57</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col0\" class=\"data row15 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col1\" class=\"data row15 col1\" >57</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col2\" class=\"data row15 col2\" >3946518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col3\" class=\"data row15 col3\" >4347023</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col4\" class=\"data row15 col4\" >400505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row15_col5\" class=\"data row15 col5\" >10.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row16\" class=\"row_heading level0 row16\" >58</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col0\" class=\"data row16 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col1\" class=\"data row16 col1\" >58</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col2\" class=\"data row16 col2\" >3802447</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col3\" class=\"data row16 col3\" >4191360</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col4\" class=\"data row16 col4\" >388913</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row16_col5\" class=\"data row16 col5\" >10.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row17\" class=\"row_heading level0 row17\" >169</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col0\" class=\"data row17 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col1\" class=\"data row17 col1\" >67</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col2\" class=\"data row17 col2\" >1270145</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col3\" class=\"data row17 col3\" >1652998</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col4\" class=\"data row17 col4\" >382853</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row17_col5\" class=\"data row17 col5\" >30.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row18\" class=\"row_heading level0 row18\" >270</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col0\" class=\"data row18 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col1\" class=\"data row18 col1\" >66</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col2\" class=\"data row18 col2\" >1381541</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col3\" class=\"data row18 col3\" >1758337</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col4\" class=\"data row18 col4\" >376796</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row18_col5\" class=\"data row18 col5\" >27.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row19\" class=\"row_heading level0 row19\" >269</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col0\" class=\"data row19 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col1\" class=\"data row19 col1\" >65</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col2\" class=\"data row19 col2\" >1405839</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col3\" class=\"data row19 col3\" >1776052</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col4\" class=\"data row19 col4\" >370213</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row19_col5\" class=\"data row19 col5\" >26.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row20\" class=\"row_heading level0 row20\" >166</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col0\" class=\"data row20 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col1\" class=\"data row20 col1\" >64</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col2\" class=\"data row20 col2\" >1291833</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col3\" class=\"data row20 col3\" >1660815</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col4\" class=\"data row20 col4\" >368982</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row20_col5\" class=\"data row20 col5\" >28.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row21\" class=\"row_heading level0 row21\" >60</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col0\" class=\"data row21 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col1\" class=\"data row21 col1\" >60</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col2\" class=\"data row21 col2\" >3616721</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col3\" class=\"data row21 col3\" >3985598</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col4\" class=\"data row21 col4\" >368877</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row21_col5\" class=\"data row21 col5\" >10.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row22\" class=\"row_heading level0 row22\" >69</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col0\" class=\"data row22 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col1\" class=\"data row22 col1\" >69</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col2\" class=\"data row22 col2\" >2167830</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col3\" class=\"data row22 col3\" >2534295</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col4\" class=\"data row22 col4\" >366465</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row22_col5\" class=\"data row22 col5\" >16.90%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row23\" class=\"row_heading level0 row23\" >32</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col0\" class=\"data row23 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col1\" class=\"data row23 col1\" >32</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col2\" class=\"data row23 col2\" >3967602</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col3\" class=\"data row23 col3\" >4323951</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col4\" class=\"data row23 col4\" >356349</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row23_col5\" class=\"data row23 col5\" >8.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row24\" class=\"row_heading level0 row24\" >168</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col0\" class=\"data row24 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col1\" class=\"data row24 col1\" >66</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col2\" class=\"data row24 col2\" >1239794</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col3\" class=\"data row24 col3\" >1588723</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col4\" class=\"data row24 col4\" >348929</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row24_col5\" class=\"data row24 col5\" >28.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row25\" class=\"row_heading level0 row25\" >33</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col0\" class=\"data row25 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col1\" class=\"data row25 col1\" >33</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col2\" class=\"data row25 col2\" >3933581</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col3\" class=\"data row25 col3\" >4278664</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col4\" class=\"data row25 col4\" >345083</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row25_col5\" class=\"data row25 col5\" >8.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row26\" class=\"row_heading level0 row26\" >167</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col0\" class=\"data row26 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col1\" class=\"data row26 col1\" >65</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col2\" class=\"data row26 col2\" >1272686</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col3\" class=\"data row26 col3\" >1606772</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col4\" class=\"data row26 col4\" >334086</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row26_col5\" class=\"data row26 col5\" >26.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row27\" class=\"row_heading level0 row27\" >22</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col0\" class=\"data row27 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col1\" class=\"data row27 col1\" >22</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col2\" class=\"data row27 col2\" >4287005</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col3\" class=\"data row27 col3\" >4615729</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col4\" class=\"data row27 col4\" >328724</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row27_col5\" class=\"data row27 col5\" >7.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row28\" class=\"row_heading level0 row28\" >61</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col0\" class=\"data row28 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col1\" class=\"data row28 col1\" >61</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col2\" class=\"data row28 col2\" >3520109</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col3\" class=\"data row28 col3\" >3834367</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col4\" class=\"data row28 col4\" >314258</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row28_col5\" class=\"data row28 col5\" >8.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row29\" class=\"row_heading level0 row29\" >72</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col0\" class=\"data row29 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col1\" class=\"data row29 col1\" >72</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col2\" class=\"data row29 col2\" >1883820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col3\" class=\"data row29 col3\" >2193945</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col4\" class=\"data row29 col4\" >310125</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row29_col5\" class=\"data row29 col5\" >16.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row30\" class=\"row_heading level0 row30\" >56</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col0\" class=\"data row30 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col1\" class=\"data row30 col1\" >56</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col2\" class=\"data row30 col2\" >4093136</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col3\" class=\"data row30 col3\" >4395949</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col4\" class=\"data row30 col4\" >302813</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row30_col5\" class=\"data row30 col5\" >7.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row31\" class=\"row_heading level0 row31\" >275</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col0\" class=\"data row31 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col1\" class=\"data row31 col1\" >71</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col2\" class=\"data row31 col2\" >1050349</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col3\" class=\"data row31 col3\" >1350590</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col4\" class=\"data row31 col4\" >300241</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row31_col5\" class=\"data row31 col5\" >28.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row32\" class=\"row_heading level0 row32\" >54</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col0\" class=\"data row32 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col1\" class=\"data row32 col1\" >54</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col2\" class=\"data row32 col2\" >4288447</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col3\" class=\"data row32 col3\" >4574760</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col4\" class=\"data row32 col4\" >286313</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row32_col5\" class=\"data row32 col5\" >6.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row33\" class=\"row_heading level0 row33\" >136</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col0\" class=\"data row33 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col1\" class=\"data row33 col1\" >34</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col2\" class=\"data row33 col2\" >1908731</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col3\" class=\"data row33 col3\" >2192877</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col4\" class=\"data row33 col4\" >284146</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row33_col5\" class=\"data row33 col5\" >14.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row34\" class=\"row_heading level0 row34\" >31</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col0\" class=\"data row34 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col1\" class=\"data row34 col1\" >31</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col2\" class=\"data row34 col2\" >4042516</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col3\" class=\"data row34 col3\" >4323217</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col4\" class=\"data row34 col4\" >280701</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row34_col5\" class=\"data row34 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row35\" class=\"row_heading level0 row35\" >173</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col0\" class=\"data row35 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col1\" class=\"data row35 col1\" >71</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col2\" class=\"data row35 col2\" >903258</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col3\" class=\"data row35 col3\" >1169115</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col4\" class=\"data row35 col4\" >265857</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row35_col5\" class=\"data row35 col5\" >29.43%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row36\" class=\"row_heading level0 row36\" >238</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col0\" class=\"data row36 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col1\" class=\"data row36 col1\" >34</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col2\" class=\"data row36 col2\" >1913458</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col3\" class=\"data row36 col3\" >2171871</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col4\" class=\"data row36 col4\" >258413</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row36_col5\" class=\"data row36 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row37\" class=\"row_heading level0 row37\" >73</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col0\" class=\"data row37 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col1\" class=\"data row37 col1\" >73</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col2\" class=\"data row37 col2\" >1750304</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col3\" class=\"data row37 col3\" >2001700</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col4\" class=\"data row37 col4\" >251396</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row37_col5\" class=\"data row37 col5\" >14.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row38\" class=\"row_heading level0 row38\" >125</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col0\" class=\"data row38 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col1\" class=\"data row38 col1\" >23</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col2\" class=\"data row38 col2\" >2151068</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col3\" class=\"data row38 col3\" >2402294</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col4\" class=\"data row38 col4\" >251226</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row38_col5\" class=\"data row38 col5\" >11.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row39\" class=\"row_heading level0 row39\" >26</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col0\" class=\"data row39 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col1\" class=\"data row39 col1\" >26</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col2\" class=\"data row39 col2\" >4160806</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col3\" class=\"data row39 col3\" >4408043</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col4\" class=\"data row39 col4\" >247237</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row39_col5\" class=\"data row39 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row40\" class=\"row_heading level0 row40\" >43</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col0\" class=\"data row40 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col1\" class=\"data row40 col1\" >43</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col2\" class=\"data row40 col2\" >4093844</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col3\" class=\"data row40 col3\" >4333850</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col4\" class=\"data row40 col4\" >240006</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row40_col5\" class=\"data row40 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row41\" class=\"row_heading level0 row41\" >263</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col0\" class=\"data row41 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col1\" class=\"data row41 col1\" >59</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col2\" class=\"data row41 col2\" >1914774</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col3\" class=\"data row41 col3\" >2148934</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col4\" class=\"data row41 col4\" >234160</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row41_col5\" class=\"data row41 col5\" >12.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row42\" class=\"row_heading level0 row42\" >227</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col0\" class=\"data row42 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col1\" class=\"data row42 col1\" >23</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col2\" class=\"data row42 col2\" >2066160</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col3\" class=\"data row42 col3\" >2299862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col4\" class=\"data row42 col4\" >233702</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row42_col5\" class=\"data row42 col5\" >11.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row43\" class=\"row_heading level0 row43\" >126</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col0\" class=\"data row43 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col1\" class=\"data row43 col1\" >24</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col2\" class=\"data row43 col2\" >2161347</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col3\" class=\"data row43 col3\" >2393037</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col4\" class=\"data row43 col4\" >231690</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row43_col5\" class=\"data row43 col5\" >10.72%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row44\" class=\"row_heading level0 row44\" >161</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col0\" class=\"data row44 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col1\" class=\"data row44 col1\" >59</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col2\" class=\"data row44 col2\" >1779480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col3\" class=\"data row44 col3\" >2006587</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col4\" class=\"data row44 col4\" >227107</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row44_col5\" class=\"data row44 col5\" >12.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row45\" class=\"row_heading level0 row45\" >25</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col0\" class=\"data row45 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col1\" class=\"data row45 col1\" >25</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col2\" class=\"data row45 col2\" >4289428</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col3\" class=\"data row45 col3\" >4511370</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col4\" class=\"data row45 col4\" >221942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row45_col5\" class=\"data row45 col5\" >5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row46\" class=\"row_heading level0 row46\" >228</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col0\" class=\"data row46 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col1\" class=\"data row46 col1\" >24</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col2\" class=\"data row46 col2\" >2082255</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col3\" class=\"data row46 col3\" >2302374</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col4\" class=\"data row46 col4\" >220119</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row46_col5\" class=\"data row46 col5\" >10.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row47\" class=\"row_heading level0 row47\" >68</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col0\" class=\"data row47 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col1\" class=\"data row47 col1\" >68</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col2\" class=\"data row47 col2\" >2359816</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col3\" class=\"data row47 col3\" >2572359</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col4\" class=\"data row47 col4\" >212543</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row47_col5\" class=\"data row47 col5\" >9.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row48\" class=\"row_heading level0 row48\" >76</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col0\" class=\"data row48 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col1\" class=\"data row48 col1\" >76</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col2\" class=\"data row48 col2\" >1481680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col3\" class=\"data row48 col3\" >1693674</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col4\" class=\"data row48 col4\" >211994</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row48_col5\" class=\"data row48 col5\" >14.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row49\" class=\"row_heading level0 row49\" >44</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col0\" class=\"data row49 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col1\" class=\"data row49 col1\" >44</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col2\" class=\"data row49 col2\" >4178508</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col3\" class=\"data row49 col3\" >4390283</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col4\" class=\"data row49 col4\" >211775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row49_col5\" class=\"data row49 col5\" >5.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row50\" class=\"row_heading level0 row50\" >274</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col0\" class=\"data row50 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col1\" class=\"data row50 col1\" >70</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col2\" class=\"data row50 col2\" >1108504</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col3\" class=\"data row50 col3\" >1316930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col4\" class=\"data row50 col4\" >208426</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row50_col5\" class=\"data row50 col5\" >18.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row51\" class=\"row_heading level0 row51\" >74</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col0\" class=\"data row51 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col1\" class=\"data row51 col1\" >74</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col2\" class=\"data row51 col2\" >1685995</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col3\" class=\"data row51 col3\" >1889513</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col4\" class=\"data row51 col4\" >203518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row51_col5\" class=\"data row51 col5\" >12.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row52\" class=\"row_heading level0 row52\" >261</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col0\" class=\"data row52 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col1\" class=\"data row52 col1\" >57</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col2\" class=\"data row52 col2\" >2036521</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col3\" class=\"data row52 col3\" >2237219</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col4\" class=\"data row52 col4\" >200698</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row52_col5\" class=\"data row52 col5\" >9.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row53\" class=\"row_heading level0 row53\" >262</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col0\" class=\"data row53 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col1\" class=\"data row53 col1\" >58</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col2\" class=\"data row53 col2\" >1963767</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col3\" class=\"data row53 col3\" >2163908</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col4\" class=\"data row53 col4\" >200141</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row53_col5\" class=\"data row53 col5\" >10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row54\" class=\"row_heading level0 row54\" >159</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col0\" class=\"data row54 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col1\" class=\"data row54 col1\" >57</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col2\" class=\"data row54 col2\" >1909997</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col3\" class=\"data row54 col3\" >2109804</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col4\" class=\"data row54 col4\" >199807</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row54_col5\" class=\"data row54 col5\" >10.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row55\" class=\"row_heading level0 row55\" >264</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col0\" class=\"data row55 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col1\" class=\"data row55 col1\" >60</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col2\" class=\"data row55 col2\" >1874501</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col3\" class=\"data row55 col3\" >2071869</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col4\" class=\"data row55 col4\" >197368</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row55_col5\" class=\"data row55 col5\" >10.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row56\" class=\"row_heading level0 row56\" >172</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col0\" class=\"data row56 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col1\" class=\"data row56 col1\" >70</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col2\" class=\"data row56 col2\" >954073</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col3\" class=\"data row56 col3\" >1148508</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col4\" class=\"data row56 col4\" >194435</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row56_col5\" class=\"data row56 col5\" >20.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row57\" class=\"row_heading level0 row57\" >62</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col0\" class=\"data row57 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col1\" class=\"data row57 col1\" >62</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col2\" class=\"data row57 col2\" >3495059</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col3\" class=\"data row57 col3\" >3685282</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col4\" class=\"data row57 col4\" >190223</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row57_col5\" class=\"data row57 col5\" >5.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row58\" class=\"row_heading level0 row58\" >160</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col0\" class=\"data row58 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col1\" class=\"data row58 col1\" >58</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col2\" class=\"data row58 col2\" >1838680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col3\" class=\"data row58 col3\" >2027452</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col4\" class=\"data row58 col4\" >188772</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row58_col5\" class=\"data row58 col5\" >10.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row59\" class=\"row_heading level0 row59\" >36</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col0\" class=\"data row59 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col1\" class=\"data row59 col1\" >36</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col2\" class=\"data row59 col2\" >3830199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col3\" class=\"data row59 col3\" >4016711</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col4\" class=\"data row59 col4\" >186512</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row59_col5\" class=\"data row59 col5\" >4.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row60\" class=\"row_heading level0 row60\" >273</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col0\" class=\"data row60 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col1\" class=\"data row60 col1\" >69</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col2\" class=\"data row60 col2\" >1161048</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col3\" class=\"data row60 col3\" >1347423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col4\" class=\"data row60 col4\" >186375</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row60_col5\" class=\"data row60 col5\" >16.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row61\" class=\"row_heading level0 row61\" >124</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col0\" class=\"data row61 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col1\" class=\"data row61 col1\" >22</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col2\" class=\"data row61 col2\" >2188199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col3\" class=\"data row61 col3\" >2370459</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col4\" class=\"data row61 col4\" >182260</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row61_col5\" class=\"data row61 col5\" >8.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row62\" class=\"row_heading level0 row62\" >29</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col0\" class=\"data row62 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col1\" class=\"data row62 col1\" >29</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col2\" class=\"data row62 col2\" >4210286</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col3\" class=\"data row62 col3\" >4391788</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col4\" class=\"data row62 col4\" >181502</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row62_col5\" class=\"data row62 col5\" >4.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row63\" class=\"row_heading level0 row63\" >134</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col0\" class=\"data row63 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col1\" class=\"data row63 col1\" >32</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col2\" class=\"data row63 col2\" >1986147</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col3\" class=\"data row63 col3\" >2167557</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col4\" class=\"data row63 col4\" >181410</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row63_col5\" class=\"data row63 col5\" >9.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row64\" class=\"row_heading level0 row64\" >171</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col0\" class=\"data row64 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col1\" class=\"data row64 col1\" >69</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col2\" class=\"data row64 col2\" >1006782</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col3\" class=\"data row64 col3\" >1186872</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col4\" class=\"data row64 col4\" >180090</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row64_col5\" class=\"data row64 col5\" >17.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row65\" class=\"row_heading level0 row65\" >135</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col0\" class=\"data row65 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col1\" class=\"data row65 col1\" >33</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col2\" class=\"data row65 col2\" >1963645</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col3\" class=\"data row65 col3\" >2141552</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col4\" class=\"data row65 col4\" >177907</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row65_col5\" class=\"data row65 col5\" >9.06%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row66\" class=\"row_heading level0 row66\" >236</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col0\" class=\"data row66 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col1\" class=\"data row66 col1\" >32</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col2\" class=\"data row66 col2\" >1981455</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col3\" class=\"data row66 col3\" >2156394</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col4\" class=\"data row66 col4\" >174939</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row66_col5\" class=\"data row66 col5\" >8.83%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row67\" class=\"row_heading level0 row67\" >162</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col0\" class=\"data row67 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col1\" class=\"data row67 col1\" >60</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col2\" class=\"data row67 col2\" >1742220</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col3\" class=\"data row67 col3\" >1913729</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col4\" class=\"data row67 col4\" >171509</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row67_col5\" class=\"data row67 col5\" >9.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row68\" class=\"row_heading level0 row68\" >265</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col0\" class=\"data row68 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col1\" class=\"data row68 col1\" >61</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col2\" class=\"data row68 col2\" >1828708</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col3\" class=\"data row68 col3\" >1997711</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col4\" class=\"data row68 col4\" >169003</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row68_col5\" class=\"data row68 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row69\" class=\"row_heading level0 row69\" >237</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col0\" class=\"data row69 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col1\" class=\"data row69 col1\" >33</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col2\" class=\"data row69 col2\" >1969936</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col3\" class=\"data row69 col3\" >2137112</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col4\" class=\"data row69 col4\" >167176</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row69_col5\" class=\"data row69 col5\" >8.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row70\" class=\"row_heading level0 row70\" >55</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col0\" class=\"data row70 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col1\" class=\"data row70 col1\" >55</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col2\" class=\"data row70 col2\" >4258970</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col3\" class=\"data row70 col3\" >4421856</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col4\" class=\"data row70 col4\" >162886</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row70_col5\" class=\"data row70 col5\" >3.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row71\" class=\"row_heading level0 row71\" >276</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col0\" class=\"data row71 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col1\" class=\"data row71 col1\" >72</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col2\" class=\"data row71 col2\" >1021291</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col3\" class=\"data row71 col3\" >1183363</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col4\" class=\"data row71 col4\" >162072</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row71_col5\" class=\"data row71 col5\" >15.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row72\" class=\"row_heading level0 row72\" >158</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col0\" class=\"data row72 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col1\" class=\"data row72 col1\" >56</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col2\" class=\"data row72 col2\" >1984452</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col3\" class=\"data row72 col3\" >2140940</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col4\" class=\"data row72 col4\" >156488</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row72_col5\" class=\"data row72 col5\" >7.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row73\" class=\"row_heading level0 row73\" >156</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col0\" class=\"data row73 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col1\" class=\"data row73 col1\" >54</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col2\" class=\"data row73 col2\" >2091640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col3\" class=\"data row73 col3\" >2242757</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col4\" class=\"data row73 col4\" >151117</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row73_col5\" class=\"data row73 col5\" >7.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row74\" class=\"row_heading level0 row74\" >174</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col0\" class=\"data row74 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col1\" class=\"data row74 col1\" >72</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col2\" class=\"data row74 col2\" >862529</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col3\" class=\"data row74 col3\" >1010582</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col4\" class=\"data row74 col4\" >148053</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row74_col5\" class=\"data row74 col5\" >17.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row75\" class=\"row_heading level0 row75\" >35</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col0\" class=\"data row75 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col1\" class=\"data row75 col1\" >35</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col2\" class=\"data row75 col2\" >3948335</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col3\" class=\"data row75 col3\" >4095782</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col4\" class=\"data row75 col4\" >147447</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row75_col5\" class=\"data row75 col5\" >3.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row76\" class=\"row_heading level0 row76\" >226</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col0\" class=\"data row76 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col1\" class=\"data row76 col1\" >22</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col2\" class=\"data row76 col2\" >2098806</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col3\" class=\"data row76 col3\" >2245270</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col4\" class=\"data row76 col4\" >146464</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row76_col5\" class=\"data row76 col5\" >6.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row77\" class=\"row_heading level0 row77\" >260</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col0\" class=\"data row77 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col1\" class=\"data row77 col1\" >56</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col2\" class=\"data row77 col2\" >2108684</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col3\" class=\"data row77 col3\" >2255009</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col4\" class=\"data row77 col4\" >146325</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row77_col5\" class=\"data row77 col5\" >6.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row78\" class=\"row_heading level0 row78\" >133</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col0\" class=\"data row78 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col1\" class=\"data row78 col1\" >31</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col2\" class=\"data row78 col2\" >2026439</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col3\" class=\"data row78 col3\" >2171839</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col4\" class=\"data row78 col4\" >145400</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row78_col5\" class=\"data row78 col5\" >7.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row79\" class=\"row_heading level0 row79\" >163</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col0\" class=\"data row79 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col1\" class=\"data row79 col1\" >61</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col2\" class=\"data row79 col2\" >1691401</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col3\" class=\"data row79 col3\" >1836656</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col4\" class=\"data row79 col4\" >145255</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row79_col5\" class=\"data row79 col5\" >8.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row80\" class=\"row_heading level0 row80\" >75</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col0\" class=\"data row80 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col1\" class=\"data row80 col1\" >75</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col2\" class=\"data row80 col2\" >1631878</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col3\" class=\"data row80 col3\" >1773756</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col4\" class=\"data row80 col4\" >141878</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row80_col5\" class=\"data row80 col5\" >8.69%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row81\" class=\"row_heading level0 row81\" >128</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col0\" class=\"data row81 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col1\" class=\"data row81 col1\" >26</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col2\" class=\"data row81 col2\" >2102331</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col3\" class=\"data row81 col3\" >2240881</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col4\" class=\"data row81 col4\" >138550</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row81_col5\" class=\"data row81 col5\" >6.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row82\" class=\"row_heading level0 row82\" >235</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col0\" class=\"data row82 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col1\" class=\"data row82 col1\" >31</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col2\" class=\"data row82 col2\" >2016077</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col3\" class=\"data row82 col3\" >2151378</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col4\" class=\"data row82 col4\" >135301</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row82_col5\" class=\"data row82 col5\" >6.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row83\" class=\"row_heading level0 row83\" >258</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col0\" class=\"data row83 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col1\" class=\"data row83 col1\" >54</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col2\" class=\"data row83 col2\" >2196807</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col3\" class=\"data row83 col3\" >2332003</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col4\" class=\"data row83 col4\" >135196</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row83_col5\" class=\"data row83 col5\" >6.15%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row84\" class=\"row_heading level0 row84\" >277</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col0\" class=\"data row84 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col1\" class=\"data row84 col1\" >73</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col2\" class=\"data row84 col2\" >955658</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col3\" class=\"data row84 col3\" >1089027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col4\" class=\"data row84 col4\" >133369</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row84_col5\" class=\"data row84 col5\" >13.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row85\" class=\"row_heading level0 row85\" >247</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col0\" class=\"data row85 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col1\" class=\"data row85 col1\" >43</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col2\" class=\"data row85 col2\" >2062862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col3\" class=\"data row85 col3\" >2185890</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col4\" class=\"data row85 col4\" >123028</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row85_col5\" class=\"data row85 col5\" >5.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row86\" class=\"row_heading level0 row86\" >127</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col0\" class=\"data row86 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col1\" class=\"data row86 col1\" >25</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col2\" class=\"data row86 col2\" >2177131</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col3\" class=\"data row86 col3\" >2296875</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col4\" class=\"data row86 col4\" >119744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row86_col5\" class=\"data row86 col5\" >5.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row87\" class=\"row_heading level0 row87\" >175</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col0\" class=\"data row87 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col1\" class=\"data row87 col1\" >73</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col2\" class=\"data row87 col2\" >794646</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col3\" class=\"data row87 col3\" >912673</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col4\" class=\"data row87 col4\" >118027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row87_col5\" class=\"data row87 col5\" >14.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row88\" class=\"row_heading level0 row88\" >145</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col0\" class=\"data row88 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col1\" class=\"data row88 col1\" >43</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col2\" class=\"data row88 col2\" >2030982</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col3\" class=\"data row88 col3\" >2147960</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col4\" class=\"data row88 col4\" >116978</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row88_col5\" class=\"data row88 col5\" >5.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row89\" class=\"row_heading level0 row89\" >7</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col0\" class=\"data row89 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col1\" class=\"data row89 col1\" >7</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col2\" class=\"data row89 col2\" >4043046</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col3\" class=\"data row89 col3\" >4155326</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col4\" class=\"data row89 col4\" >112280</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row89_col5\" class=\"data row89 col5\" >2.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row90\" class=\"row_heading level0 row90\" >146</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col0\" class=\"data row90 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col1\" class=\"data row90 col1\" >44</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col2\" class=\"data row90 col2\" >2074572</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col3\" class=\"data row90 col3\" >2184448</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col4\" class=\"data row90 col4\" >109876</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row90_col5\" class=\"data row90 col5\" >5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row91\" class=\"row_heading level0 row91\" >230</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col0\" class=\"data row91 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col1\" class=\"data row91 col1\" >26</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col2\" class=\"data row91 col2\" >2058475</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col3\" class=\"data row91 col3\" >2167162</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col4\" class=\"data row91 col4\" >108687</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row91_col5\" class=\"data row91 col5\" >5.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row92\" class=\"row_heading level0 row92\" >280</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col0\" class=\"data row92 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col1\" class=\"data row92 col1\" >76</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col2\" class=\"data row92 col2\" >828129</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col3\" class=\"data row92 col3\" >935833</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col4\" class=\"data row92 col4\" >107704</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row92_col5\" class=\"data row92 col5\" >13.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row93\" class=\"row_heading level0 row93\" >28</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col0\" class=\"data row93 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col1\" class=\"data row93 col1\" >28</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col2\" class=\"data row93 col2\" >4247541</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col3\" class=\"data row93 col3\" >4355240</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col4\" class=\"data row93 col4\" >107699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row93_col5\" class=\"data row93 col5\" >2.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row94\" class=\"row_heading level0 row94\" >131</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col0\" class=\"data row94 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col1\" class=\"data row94 col1\" >29</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col2\" class=\"data row94 col2\" >2112313</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col3\" class=\"data row94 col3\" >2219872</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col4\" class=\"data row94 col4\" >107559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row94_col5\" class=\"data row94 col5\" >5.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row95\" class=\"row_heading level0 row95\" >272</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col0\" class=\"data row95 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col1\" class=\"data row95 col1\" >68</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col2\" class=\"data row95 col2\" >1254117</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col3\" class=\"data row95 col3\" >1361081</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col4\" class=\"data row95 col4\" >106964</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row95_col5\" class=\"data row95 col5\" >8.53%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row96\" class=\"row_heading level0 row96\" >77</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col0\" class=\"data row96 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col1\" class=\"data row96 col1\" >77</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col2\" class=\"data row96 col2\" >1449173</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col3\" class=\"data row96 col3\" >1556104</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col4\" class=\"data row96 col4\" >106931</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row96_col5\" class=\"data row96 col5\" >7.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row97\" class=\"row_heading level0 row97\" >266</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col0\" class=\"data row97 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col1\" class=\"data row97 col1\" >62</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col2\" class=\"data row97 col2\" >1815999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col3\" class=\"data row97 col3\" >1922402</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col4\" class=\"data row97 col4\" >106403</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row97_col5\" class=\"data row97 col5\" >5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row98\" class=\"row_heading level0 row98\" >170</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col0\" class=\"data row98 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col1\" class=\"data row98 col1\" >68</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col2\" class=\"data row98 col2\" >1105699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col3\" class=\"data row98 col3\" >1211278</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col4\" class=\"data row98 col4\" >105579</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row98_col5\" class=\"data row98 col5\" >9.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row99\" class=\"row_heading level0 row99\" >278</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col0\" class=\"data row99 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col1\" class=\"data row99 col1\" >74</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col2\" class=\"data row99 col2\" >927165</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col3\" class=\"data row99 col3\" >1032543</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col4\" class=\"data row99 col4\" >105378</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row99_col5\" class=\"data row99 col5\" >11.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row100\" class=\"row_heading level0 row100\" >21</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col0\" class=\"data row100 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col1\" class=\"data row100 col1\" >21</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col2\" class=\"data row100 col2\" >4387956</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col3\" class=\"data row100 col3\" >4492373</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col4\" class=\"data row100 col4\" >104417</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row100_col5\" class=\"data row100 col5\" >2.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row101\" class=\"row_heading level0 row101\" >178</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col0\" class=\"data row101 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col1\" class=\"data row101 col1\" >76</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col2\" class=\"data row101 col2\" >653551</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col3\" class=\"data row101 col3\" >757841</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col4\" class=\"data row101 col4\" >104290</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row101_col5\" class=\"data row101 col5\" >15.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row102\" class=\"row_heading level0 row102\" >229</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col0\" class=\"data row102 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col1\" class=\"data row102 col1\" >25</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col2\" class=\"data row102 col2\" >2112297</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col3\" class=\"data row102 col3\" >2214495</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col4\" class=\"data row102 col4\" >102198</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row102_col5\" class=\"data row102 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row103\" class=\"row_heading level0 row103\" >248</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col0\" class=\"data row103 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col1\" class=\"data row103 col1\" >44</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col2\" class=\"data row103 col2\" >2103936</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col3\" class=\"data row103 col3\" >2205835</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col4\" class=\"data row103 col4\" >101899</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row103_col5\" class=\"data row103 col5\" >4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row104\" class=\"row_heading level0 row104\" >138</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col0\" class=\"data row104 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col1\" class=\"data row104 col1\" >36</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col2\" class=\"data row104 col2\" >1907408</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col3\" class=\"data row104 col3\" >2005880</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col4\" class=\"data row104 col4\" >98472</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row104_col5\" class=\"data row104 col5\" >5.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row105\" class=\"row_heading level0 row105\" >176</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col0\" class=\"data row105 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col1\" class=\"data row105 col1\" >74</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col2\" class=\"data row105 col2\" >758830</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col3\" class=\"data row105 col3\" >856970</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col4\" class=\"data row105 col4\" >98140</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row105_col5\" class=\"data row105 col5\" >12.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row106\" class=\"row_heading level0 row106\" >27</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col0\" class=\"data row106 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col1\" class=\"data row106 col1\" >27</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col2\" class=\"data row106 col2\" >4237026</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col3\" class=\"data row106 col3\" >4334806</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col4\" class=\"data row106 col4\" >97780</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row106_col5\" class=\"data row106 col5\" >2.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row107\" class=\"row_heading level0 row107\" >53</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col0\" class=\"data row107 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col1\" class=\"data row107 col1\" >53</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col2\" class=\"data row107 col2\" >4439403</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col3\" class=\"data row107 col3\" >4535430</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col4\" class=\"data row107 col4\" >96027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row107_col5\" class=\"data row107 col5\" >2.16%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row108\" class=\"row_heading level0 row108\" >8</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col0\" class=\"data row108 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col1\" class=\"data row108 col1\" >8</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col2\" class=\"data row108 col2\" >4025604</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col3\" class=\"data row108 col3\" >4120903</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col4\" class=\"data row108 col4\" >95299</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row108_col5\" class=\"data row108 col5\" >2.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row109\" class=\"row_heading level0 row109\" >14</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col0\" class=\"data row109 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col1\" class=\"data row109 col1\" >14</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col2\" class=\"data row109 col2\" >4145614</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col3\" class=\"data row109 col3\" >4233839</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col4\" class=\"data row109 col4\" >88225</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row109_col5\" class=\"data row109 col5\" >2.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row110\" class=\"row_heading level0 row110\" >240</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col0\" class=\"data row110 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col1\" class=\"data row110 col1\" >36</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col2\" class=\"data row110 col2\" >1922791</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col3\" class=\"data row110 col3\" >2010831</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col4\" class=\"data row110 col4\" >88040</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row110_col5\" class=\"data row110 col5\" >4.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row111\" class=\"row_heading level0 row111\" >164</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col0\" class=\"data row111 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col1\" class=\"data row111 col1\" >62</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col2\" class=\"data row111 col2\" >1679060</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col3\" class=\"data row111 col3\" >1762880</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col4\" class=\"data row111 col4\" >83820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row111_col5\" class=\"data row111 col5\" >4.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row112\" class=\"row_heading level0 row112\" >157</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col0\" class=\"data row112 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col1\" class=\"data row112 col1\" >55</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col2\" class=\"data row112 col2\" >2075199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col3\" class=\"data row112 col3\" >2158427</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col4\" class=\"data row112 col4\" >83228</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row112_col5\" class=\"data row112 col5\" >4.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row113\" class=\"row_heading level0 row113\" >91</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col0\" class=\"data row113 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col1\" class=\"data row113 col1\" >91</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col2\" class=\"data row113 col2\" >344442</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col3\" class=\"data row113 col3\" >425314</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col4\" class=\"data row113 col4\" >80872</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row113_col5\" class=\"data row113 col5\" >23.48%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row114\" class=\"row_heading level0 row114\" >37</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col0\" class=\"data row114 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col1\" class=\"data row114 col1\" >37</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col2\" class=\"data row114 col2\" >3896766</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col3\" class=\"data row114 col3\" >3976750</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col4\" class=\"data row114 col4\" >79984</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row114_col5\" class=\"data row114 col5\" >2.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row115\" class=\"row_heading level0 row115\" >259</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col0\" class=\"data row115 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col1\" class=\"data row115 col1\" >55</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col2\" class=\"data row115 col2\" >2183771</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col3\" class=\"data row115 col3\" >2263429</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col4\" class=\"data row115 col4\" >79658</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row115_col5\" class=\"data row115 col5\" >3.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row116\" class=\"row_heading level0 row116\" >78</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col0\" class=\"data row116 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col1\" class=\"data row116 col1\" >78</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col2\" class=\"data row116 col2\" >1402182</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col3\" class=\"data row116 col3\" >1480611</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col4\" class=\"data row116 col4\" >78429</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row116_col5\" class=\"data row116 col5\" >5.59%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row117\" class=\"row_heading level0 row117\" >177</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col0\" class=\"data row117 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col1\" class=\"data row117 col1\" >75</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col2\" class=\"data row117 col2\" >725663</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col3\" class=\"data row117 col3\" >802960</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col4\" class=\"data row117 col4\" >77297</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row117_col5\" class=\"data row117 col5\" >10.65%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row118\" class=\"row_heading level0 row118\" >239</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col0\" class=\"data row118 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col1\" class=\"data row118 col1\" >35</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col2\" class=\"data row118 col2\" >1973699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col3\" class=\"data row118 col3\" >2047905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col4\" class=\"data row118 col4\" >74206</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row118_col5\" class=\"data row118 col5\" >3.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row119\" class=\"row_heading level0 row119\" >233</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col0\" class=\"data row119 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col1\" class=\"data row119 col1\" >29</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col2\" class=\"data row119 col2\" >2097973</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col3\" class=\"data row119 col3\" >2171916</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col4\" class=\"data row119 col4\" >73943</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row119_col5\" class=\"data row119 col5\" >3.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row120\" class=\"row_heading level0 row120\" >130</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col0\" class=\"data row120 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col1\" class=\"data row120 col1\" >28</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col2\" class=\"data row120 col2\" >2134981</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col3\" class=\"data row120 col3\" >2208749</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col4\" class=\"data row120 col4\" >73768</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row120_col5\" class=\"data row120 col5\" >3.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row121\" class=\"row_heading level0 row121\" >137</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col0\" class=\"data row121 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col1\" class=\"data row121 col1\" >35</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col2\" class=\"data row121 col2\" >1974636</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col3\" class=\"data row121 col3\" >2047877</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col4\" class=\"data row121 col4\" >73241</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row121_col5\" class=\"data row121 col5\" >3.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row122\" class=\"row_heading level0 row122\" >123</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col0\" class=\"data row122 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col1\" class=\"data row122 col1\" >21</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col2\" class=\"data row122 col2\" >2241083</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col3\" class=\"data row122 col3\" >2312917</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col4\" class=\"data row122 col4\" >71834</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row122_col5\" class=\"data row122 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row123\" class=\"row_heading level0 row123\" >129</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col0\" class=\"data row123 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col1\" class=\"data row123 col1\" >27</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col2\" class=\"data row123 col2\" >2135178</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col3\" class=\"data row123 col3\" >2201518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col4\" class=\"data row123 col4\" >66340</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row123_col5\" class=\"data row123 col5\" >3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row124\" class=\"row_heading level0 row124\" >93</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col0\" class=\"data row124 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col1\" class=\"data row124 col1\" >93</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col2\" class=\"data row124 col2\" >219064</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col3\" class=\"data row124 col3\" >284885</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col4\" class=\"data row124 col4\" >65821</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row124_col5\" class=\"data row124 col5\" >30.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row125\" class=\"row_heading level0 row125\" >279</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col0\" class=\"data row125 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col1\" class=\"data row125 col1\" >75</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col2\" class=\"data row125 col2\" >906215</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col3\" class=\"data row125 col3\" >970796</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col4\" class=\"data row125 col4\" >64581</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row125_col5\" class=\"data row125 col5\" >7.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row126\" class=\"row_heading level0 row126\" >92</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col0\" class=\"data row126 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col1\" class=\"data row126 col1\" >92</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col2\" class=\"data row126 col2\" >288841</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col3\" class=\"data row126 col3\" >352912</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col4\" class=\"data row126 col4\" >64071</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row126_col5\" class=\"data row126 col5\" >22.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row127\" class=\"row_heading level0 row127\" >6</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col0\" class=\"data row127 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col1\" class=\"data row127 col1\" >6</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col2\" class=\"data row127 col2\" >4073013</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col3\" class=\"data row127 col3\" >4135930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col4\" class=\"data row127 col4\" >62917</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row127_col5\" class=\"data row127 col5\" >1.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row128\" class=\"row_heading level0 row128\" >90</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col0\" class=\"data row128 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col1\" class=\"data row128 col1\" >90</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col2\" class=\"data row128 col2\" >448324</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col3\" class=\"data row128 col3\" >511074</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col4\" class=\"data row128 col4\" >62750</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row128_col5\" class=\"data row128 col5\" >14.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row129\" class=\"row_heading level0 row129\" >109</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col0\" class=\"data row129 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col1\" class=\"data row129 col1\" >7</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col2\" class=\"data row129 col2\" >2063139</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col3\" class=\"data row129 col3\" >2122832</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col4\" class=\"data row129 col4\" >59693</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row129_col5\" class=\"data row129 col5\" >2.89%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row130\" class=\"row_heading level0 row130\" >179</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col0\" class=\"data row130 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col1\" class=\"data row130 col1\" >77</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col2\" class=\"data row130 col2\" >630867</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col3\" class=\"data row130 col3\" >689162</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col4\" class=\"data row130 col4\" >58295</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row130_col5\" class=\"data row130 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row131\" class=\"row_heading level0 row131\" >79</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col0\" class=\"data row131 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col1\" class=\"data row131 col1\" >79</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col2\" class=\"data row131 col2\" >1354912</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col3\" class=\"data row131 col3\" >1413193</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col4\" class=\"data row131 col4\" >58281</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row131_col5\" class=\"data row131 col5\" >4.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row132\" class=\"row_heading level0 row132\" >211</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col0\" class=\"data row132 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col1\" class=\"data row132 col1\" >7</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col2\" class=\"data row132 col2\" >1979907</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col3\" class=\"data row132 col3\" >2032494</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col4\" class=\"data row132 col4\" >52587</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row132_col5\" class=\"data row132 col5\" >2.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row133\" class=\"row_heading level0 row133\" >89</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col0\" class=\"data row133 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col1\" class=\"data row133 col1\" >89</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col2\" class=\"data row133 col2\" >546193</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col3\" class=\"data row133 col3\" >597828</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col4\" class=\"data row133 col4\" >51635</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row133_col5\" class=\"data row133 col5\" >9.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row134\" class=\"row_heading level0 row134\" >13</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col0\" class=\"data row134 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col1\" class=\"data row134 col1\" >13</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col2\" class=\"data row134 col2\" >4119666</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col3\" class=\"data row134 col3\" >4171030</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col4\" class=\"data row134 col4\" >51364</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row134_col5\" class=\"data row134 col5\" >1.25%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row135\" class=\"row_heading level0 row135\" >110</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col0\" class=\"data row135 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col1\" class=\"data row135 col1\" >8</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col2\" class=\"data row135 col2\" >2054462</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col3\" class=\"data row135 col3\" >2105618</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col4\" class=\"data row135 col4\" >51156</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row135_col5\" class=\"data row135 col5\" >2.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row136\" class=\"row_heading level0 row136\" >281</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col0\" class=\"data row136 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col1\" class=\"data row136 col1\" >77</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col2\" class=\"data row136 col2\" >818306</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col3\" class=\"data row136 col3\" >866942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col4\" class=\"data row136 col4\" >48636</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row136_col5\" class=\"data row136 col5\" >5.94%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row137\" class=\"row_heading level0 row137\" >155</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col0\" class=\"data row137 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col1\" class=\"data row137 col1\" >53</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col2\" class=\"data row137 col2\" >2170923</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col3\" class=\"data row137 col3\" >2219328</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col4\" class=\"data row137 col4\" >48405</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row137_col5\" class=\"data row137 col5\" >2.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row138\" class=\"row_heading level0 row138\" >295</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col0\" class=\"data row138 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col1\" class=\"data row138 col1\" >91</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col2\" class=\"data row138 col2\" >240151</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col3\" class=\"data row138 col3\" >287889</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col4\" class=\"data row138 col4\" >47738</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row138_col5\" class=\"data row138 col5\" >19.88%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row139\" class=\"row_heading level0 row139\" >257</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col0\" class=\"data row139 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col1\" class=\"data row139 col1\" >53</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col2\" class=\"data row139 col2\" >2268480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col3\" class=\"data row139 col3\" >2316102</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col4\" class=\"data row139 col4\" >47622</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row139_col5\" class=\"data row139 col5\" >2.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row140\" class=\"row_heading level0 row140\" >87</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col0\" class=\"data row140 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col1\" class=\"data row140 col1\" >87</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col2\" class=\"data row140 col2\" >721196</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col3\" class=\"data row140 col3\" >768676</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col4\" class=\"data row140 col4\" >47480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row140_col5\" class=\"data row140 col5\" >6.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row141\" class=\"row_heading level0 row141\" >84</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col0\" class=\"data row141 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col1\" class=\"data row141 col1\" >84</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col2\" class=\"data row141 col2\" >987023</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col3\" class=\"data row141 col3\" >1034369</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col4\" class=\"data row141 col4\" >47346</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row141_col5\" class=\"data row141 col5\" >4.80%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row142\" class=\"row_heading level0 row142\" >94</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col0\" class=\"data row142 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col1\" class=\"data row142 col1\" >94</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col2\" class=\"data row142 col2\" >170775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col3\" class=\"data row142 col3\" >217328</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col4\" class=\"data row142 col4\" >46553</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row142_col5\" class=\"data row142 col5\" >27.26%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row143\" class=\"row_heading level0 row143\" >218</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col0\" class=\"data row143 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col1\" class=\"data row143 col1\" >14</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col2\" class=\"data row143 col2\" >2022701</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col3\" class=\"data row143 col3\" >2068915</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col4\" class=\"data row143 col4\" >46214</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row143_col5\" class=\"data row143 col5\" >2.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row144\" class=\"row_heading level0 row144\" >180</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col0\" class=\"data row144 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col1\" class=\"data row144 col1\" >78</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col2\" class=\"data row144 col2\" >602774</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col3\" class=\"data row144 col3\" >648696</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col4\" class=\"data row144 col4\" >45922</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row144_col5\" class=\"data row144 col5\" >7.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row145\" class=\"row_heading level0 row145\" >139</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col0\" class=\"data row145 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col1\" class=\"data row145 col1\" >37</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col2\" class=\"data row145 col2\" >1934537</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col3\" class=\"data row145 col3\" >1979888</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col4\" class=\"data row145 col4\" >45351</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row145_col5\" class=\"data row145 col5\" >2.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row146\" class=\"row_heading level0 row146\" >212</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col0\" class=\"data row146 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col1\" class=\"data row146 col1\" >8</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col2\" class=\"data row146 col2\" >1971142</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col3\" class=\"data row146 col3\" >2015285</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col4\" class=\"data row146 col4\" >44143</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row146_col5\" class=\"data row146 col5\" >2.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row147\" class=\"row_heading level0 row147\" >116</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col0\" class=\"data row147 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col1\" class=\"data row147 col1\" >14</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col2\" class=\"data row147 col2\" >2122913</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col3\" class=\"data row147 col3\" >2164924</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col4\" class=\"data row147 col4\" >42011</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row147_col5\" class=\"data row147 col5\" >1.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row148\" class=\"row_heading level0 row148\" >297</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col0\" class=\"data row148 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col1\" class=\"data row148 col1\" >93</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col2\" class=\"data row148 col2\" >158882</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col3\" class=\"data row148 col3\" >199426</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col4\" class=\"data row148 col4\" >40544</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row148_col5\" class=\"data row148 col5\" >25.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row149\" class=\"row_heading level0 row149\" >296</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col0\" class=\"data row149 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col1\" class=\"data row149 col1\" >92</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col2\" class=\"data row149 col2\" >205379</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col3\" class=\"data row149 col3\" >243648</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col4\" class=\"data row149 col4\" >38269</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row149_col5\" class=\"data row149 col5\" >18.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row150\" class=\"row_heading level0 row150\" >88</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col0\" class=\"data row150 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col1\" class=\"data row150 col1\" >88</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col2\" class=\"data row150 col2\" >636657</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col3\" class=\"data row150 col3\" >673402</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col4\" class=\"data row150 col4\" >36745</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row150_col5\" class=\"data row150 col5\" >5.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row151\" class=\"row_heading level0 row151\" >181</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col0\" class=\"data row151 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col1\" class=\"data row151 col1\" >79</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col2\" class=\"data row151 col2\" >573885</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col3\" class=\"data row151 col3\" >610115</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col4\" class=\"data row151 col4\" >36230</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row151_col5\" class=\"data row151 col5\" >6.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row152\" class=\"row_heading level0 row152\" >186</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col0\" class=\"data row152 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col1\" class=\"data row152 col1\" >84</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col2\" class=\"data row152 col2\" >375685</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col3\" class=\"data row152 col3\" >410385</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col4\" class=\"data row152 col4\" >34700</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row152_col5\" class=\"data row152 col5\" >9.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row153\" class=\"row_heading level0 row153\" >241</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col0\" class=\"data row153 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col1\" class=\"data row153 col1\" >37</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col2\" class=\"data row153 col2\" >1962229</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col3\" class=\"data row153 col3\" >1996862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col4\" class=\"data row153 col4\" >34633</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row153_col5\" class=\"data row153 col5\" >1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row154\" class=\"row_heading level0 row154\" >294</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col0\" class=\"data row154 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col1\" class=\"data row154 col1\" >90</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col2\" class=\"data row154 col2\" >306925</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col3\" class=\"data row154 col3\" >341430</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col4\" class=\"data row154 col4\" >34505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row154_col5\" class=\"data row154 col5\" >11.24%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row155\" class=\"row_heading level0 row155\" >232</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col0\" class=\"data row155 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col1\" class=\"data row155 col1\" >28</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col2\" class=\"data row155 col2\" >2112560</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col3\" class=\"data row155 col3\" >2146491</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col4\" class=\"data row155 col4\" >33931</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row155_col5\" class=\"data row155 col5\" >1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row156\" class=\"row_heading level0 row156\" >193</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col0\" class=\"data row156 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col1\" class=\"data row156 col1\" >91</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col2\" class=\"data row156 col2\" >104291</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col3\" class=\"data row156 col3\" >137425</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col4\" class=\"data row156 col4\" >33134</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row156_col5\" class=\"data row156 col5\" >31.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row157\" class=\"row_heading level0 row157\" >225</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col0\" class=\"data row157 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col1\" class=\"data row157 col1\" >21</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col2\" class=\"data row157 col2\" >2146873</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col3\" class=\"data row157 col3\" >2179456</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col4\" class=\"data row157 col4\" >32583</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row157_col5\" class=\"data row157 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row158\" class=\"row_heading level0 row158\" >282</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col0\" class=\"data row158 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col1\" class=\"data row158 col1\" >78</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col2\" class=\"data row158 col2\" >799408</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col3\" class=\"data row158 col3\" >831915</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col4\" class=\"data row158 col4\" >32507</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row158_col5\" class=\"data row158 col5\" >4.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row159\" class=\"row_heading level0 row159\" >86</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col0\" class=\"data row159 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col1\" class=\"data row159 col1\" >86</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col2\" class=\"data row159 col2\" >821549</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col3\" class=\"data row159 col3\" >853723</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col4\" class=\"data row159 col4\" >32174</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row159_col5\" class=\"data row159 col5\" >3.92%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row160\" class=\"row_heading level0 row160\" >108</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col0\" class=\"data row160 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col1\" class=\"data row160 col1\" >6</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col2\" class=\"data row160 col2\" >2079410</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col3\" class=\"data row160 col3\" >2111060</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col4\" class=\"data row160 col4\" >31650</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row160_col5\" class=\"data row160 col5\" >1.52%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row161\" class=\"row_heading level0 row161\" >231</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col0\" class=\"data row161 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col1\" class=\"data row161 col1\" >27</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col2\" class=\"data row161 col2\" >2101848</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col3\" class=\"data row161 col3\" >2133288</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col4\" class=\"data row161 col4\" >31440</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row161_col5\" class=\"data row161 col5\" >1.50%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row162\" class=\"row_heading level0 row162\" >210</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col0\" class=\"data row162 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col1\" class=\"data row162 col1\" >6</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col2\" class=\"data row162 col2\" >1993603</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col3\" class=\"data row162 col3\" >2024870</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col4\" class=\"data row162 col4\" >31267</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row162_col5\" class=\"data row162 col5\" >1.57%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row163\" class=\"row_heading level0 row163\" >189</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col0\" class=\"data row163 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col1\" class=\"data row163 col1\" >87</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col2\" class=\"data row163 col2\" >253621</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col3\" class=\"data row163 col3\" >282423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col4\" class=\"data row163 col4\" >28802</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row163_col5\" class=\"data row163 col5\" >11.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row164\" class=\"row_heading level0 row164\" >298</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col0\" class=\"data row164 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col1\" class=\"data row164 col1\" >94</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col2\" class=\"data row164 col2\" >126948</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col3\" class=\"data row164 col3\" >155637</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col4\" class=\"data row164 col4\" >28689</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row164_col5\" class=\"data row164 col5\" >22.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row165\" class=\"row_heading level0 row165\" >192</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col0\" class=\"data row165 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col1\" class=\"data row165 col1\" >90</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col2\" class=\"data row165 col2\" >141399</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col3\" class=\"data row165 col3\" >169644</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col4\" class=\"data row165 col4\" >28245</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row165_col5\" class=\"data row165 col5\" >19.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row166\" class=\"row_heading level0 row166\" >217</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col0\" class=\"data row166 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col1\" class=\"data row166 col1\" >13</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col2\" class=\"data row166 col2\" >2014717</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col3\" class=\"data row166 col3\" >2042116</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col4\" class=\"data row166 col4\" >27399</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row166_col5\" class=\"data row166 col5\" >1.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row167\" class=\"row_heading level0 row167\" >293</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col0\" class=\"data row167 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col1\" class=\"data row167 col1\" >89</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col2\" class=\"data row167 col2\" >365732</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col3\" class=\"data row167 col3\" >392978</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col4\" class=\"data row167 col4\" >27246</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row167_col5\" class=\"data row167 col5\" >7.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row168\" class=\"row_heading level0 row168\" >188</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col0\" class=\"data row168 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col1\" class=\"data row168 col1\" >86</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col2\" class=\"data row168 col2\" >295396</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col3\" class=\"data row168 col3\" >322043</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col4\" class=\"data row168 col4\" >26647</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row168_col5\" class=\"data row168 col5\" >9.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row169\" class=\"row_heading level0 row169\" >194</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col0\" class=\"data row169 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col1\" class=\"data row169 col1\" >92</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col2\" class=\"data row169 col2\" >83462</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col3\" class=\"data row169 col3\" >109264</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col4\" class=\"data row169 col4\" >25802</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row169_col5\" class=\"data row169 col5\" >30.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row170\" class=\"row_heading level0 row170\" >195</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col0\" class=\"data row170 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col1\" class=\"data row170 col1\" >93</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col2\" class=\"data row170 col2\" >60182</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col3\" class=\"data row170 col3\" >85459</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col4\" class=\"data row170 col4\" >25277</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row170_col5\" class=\"data row170 col5\" >42.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row171\" class=\"row_heading level0 row171\" >95</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col0\" class=\"data row171 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col1\" class=\"data row171 col1\" >95</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col2\" class=\"data row171 col2\" >131077</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col3\" class=\"data row171 col3\" >156288</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col4\" class=\"data row171 col4\" >25211</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row171_col5\" class=\"data row171 col5\" >19.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row172\" class=\"row_heading level0 row172\" >191</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col0\" class=\"data row172 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col1\" class=\"data row172 col1\" >89</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col2\" class=\"data row172 col2\" >180461</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col3\" class=\"data row172 col3\" >204850</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col4\" class=\"data row172 col4\" >24389</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row172_col5\" class=\"data row172 col5\" >13.51%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row173\" class=\"row_heading level0 row173\" >115</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col0\" class=\"data row173 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col1\" class=\"data row173 col1\" >13</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col2\" class=\"data row173 col2\" >2104949</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col3\" class=\"data row173 col3\" >2128914</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col4\" class=\"data row173 col4\" >23965</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row173_col5\" class=\"data row173 col5\" >1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row174\" class=\"row_heading level0 row174\" >96</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col0\" class=\"data row174 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col1\" class=\"data row174 col1\" >96</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col2\" class=\"data row174 col2\" >97161</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col3\" class=\"data row174 col3\" >120485</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col4\" class=\"data row174 col4\" >23324</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row174_col5\" class=\"data row174 col5\" >24.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row175\" class=\"row_heading level0 row175\" >190</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col0\" class=\"data row175 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col1\" class=\"data row175 col1\" >88</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col2\" class=\"data row175 col2\" >216220</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col3\" class=\"data row175 col3\" >239455</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col4\" class=\"data row175 col4\" >23235</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row175_col5\" class=\"data row175 col5\" >10.75%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row176\" class=\"row_heading level0 row176\" >283</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col0\" class=\"data row176 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col1\" class=\"data row176 col1\" >79</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col2\" class=\"data row176 col2\" >781027</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col3\" class=\"data row176 col3\" >803078</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col4\" class=\"data row176 col4\" >22051</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row176_col5\" class=\"data row176 col5\" >2.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row177\" class=\"row_heading level0 row177\" >187</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col0\" class=\"data row177 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col1\" class=\"data row177 col1\" >85</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col2\" class=\"data row177 col2\" >337661</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col3\" class=\"data row177 col3\" >358342</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col4\" class=\"data row177 col4\" >20681</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row177_col5\" class=\"data row177 col5\" >6.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row178\" class=\"row_heading level0 row178\" >291</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col0\" class=\"data row178 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col1\" class=\"data row178 col1\" >87</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col2\" class=\"data row178 col2\" >467575</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col3\" class=\"data row178 col3\" >486253</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col4\" class=\"data row178 col4\" >18678</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row178_col5\" class=\"data row178 col5\" >3.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row179\" class=\"row_heading level0 row179\" >185</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col0\" class=\"data row179 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col1\" class=\"data row179 col1\" >83</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col2\" class=\"data row179 col2\" >422999</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col3\" class=\"data row179 col3\" >441530</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col4\" class=\"data row179 col4\" >18531</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row179_col5\" class=\"data row179 col5\" >4.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row180\" class=\"row_heading level0 row180\" >196</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col0\" class=\"data row180 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col1\" class=\"data row180 col1\" >94</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col2\" class=\"data row180 col2\" >43827</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col3\" class=\"data row180 col3\" >61691</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col4\" class=\"data row180 col4\" >17864</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row180_col5\" class=\"data row180 col5\" >40.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row181\" class=\"row_heading level0 row181\" >100</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col0\" class=\"data row181 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col1\" class=\"data row181 col1\" >100</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col2\" class=\"data row181 col2\" >54410</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col3\" class=\"data row181 col3\" >71626</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col4\" class=\"data row181 col4\" >17216</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row181_col5\" class=\"data row181 col5\" >31.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row182\" class=\"row_heading level0 row182\" >42</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col0\" class=\"data row182 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col1\" class=\"data row182 col1\" >42</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col2\" class=\"data row182 col2\" >4082712</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col3\" class=\"data row182 col3\" >4097698</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col4\" class=\"data row182 col4\" >14986</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row182_col5\" class=\"data row182 col5\" >0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row183\" class=\"row_heading level0 row183\" >246</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col0\" class=\"data row183 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col1\" class=\"data row183 col1\" >42</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col2\" class=\"data row183 col2\" >2050930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col3\" class=\"data row183 col3\" >2065491</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col4\" class=\"data row183 col4\" >14561</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row183_col5\" class=\"data row183 col5\" >0.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row184\" class=\"row_heading level0 row184\" >299</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col0\" class=\"data row184 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col1\" class=\"data row184 col1\" >95</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col2\" class=\"data row184 col2\" >99341</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col3\" class=\"data row184 col3\" >113732</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col4\" class=\"data row184 col4\" >14391</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row184_col5\" class=\"data row184 col5\" >14.49%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row185\" class=\"row_heading level0 row185\" >300</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col0\" class=\"data row185 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col1\" class=\"data row185 col1\" >96</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col2\" class=\"data row185 col2\" >75139</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col3\" class=\"data row185 col3\" >89432</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col4\" class=\"data row185 col4\" >14293</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row185_col5\" class=\"data row185 col5\" >19.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row186\" class=\"row_heading level0 row186\" >183</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col0\" class=\"data row186 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col1\" class=\"data row186 col1\" >81</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col2\" class=\"data row186 col2\" >496070</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col3\" class=\"data row186 col3\" >510305</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col4\" class=\"data row186 col4\" >14235</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row186_col5\" class=\"data row186 col5\" >2.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row187\" class=\"row_heading level0 row187\" >97</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col0\" class=\"data row187 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col1\" class=\"data row187 col1\" >97</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col2\" class=\"data row187 col2\" >68893</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col3\" class=\"data row187 col3\" >83089</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col4\" class=\"data row187 col4\" >14196</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row187_col5\" class=\"data row187 col5\" >20.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row188\" class=\"row_heading level0 row188\" >292</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col0\" class=\"data row188 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col1\" class=\"data row188 col1\" >88</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col2\" class=\"data row188 col2\" >420437</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col3\" class=\"data row188 col3\" >433947</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col4\" class=\"data row188 col4\" >13510</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row188_col5\" class=\"data row188 col5\" >3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row189\" class=\"row_heading level0 row189\" >184</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col0\" class=\"data row189 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col1\" class=\"data row189 col1\" >82</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col2\" class=\"data row189 col2\" >462807</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col3\" class=\"data row189 col3\" >476034</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col4\" class=\"data row189 col4\" >13227</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row189_col5\" class=\"data row189 col5\" >2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row190\" class=\"row_heading level0 row190\" >304</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col0\" class=\"data row190 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col1\" class=\"data row190 col1\" >100</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col2\" class=\"data row190 col2\" >45058</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col3\" class=\"data row190 col3\" >58008</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col4\" class=\"data row190 col4\" >12950</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row190_col5\" class=\"data row190 col5\" >28.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row191\" class=\"row_heading level0 row191\" >98</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col0\" class=\"data row191 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col1\" class=\"data row191 col1\" >98</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col2\" class=\"data row191 col2\" >47037</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col3\" class=\"data row191 col3\" >59726</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col4\" class=\"data row191 col4\" >12689</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row191_col5\" class=\"data row191 col5\" >26.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row192\" class=\"row_heading level0 row192\" >288</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col0\" class=\"data row192 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col1\" class=\"data row192 col1\" >84</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col2\" class=\"data row192 col2\" >611338</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col3\" class=\"data row192 col3\" >623984</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col4\" class=\"data row192 col4\" >12646</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row192_col5\" class=\"data row192 col5\" >2.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row193\" class=\"row_heading level0 row193\" >197</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col0\" class=\"data row193 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col1\" class=\"data row193 col1\" >95</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col2\" class=\"data row193 col2\" >31736</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col3\" class=\"data row193 col3\" >42556</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col4\" class=\"data row193 col4\" >10820</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row193_col5\" class=\"data row193 col5\" >34.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row194\" class=\"row_heading level0 row194\" >99</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col0\" class=\"data row194 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col1\" class=\"data row194 col1\" >99</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col2\" class=\"data row194 col2\" >32178</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col3\" class=\"data row194 col3\" >41468</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col4\" class=\"data row194 col4\" >9290</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row194_col5\" class=\"data row194 col5\" >28.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row195\" class=\"row_heading level0 row195\" >198</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col0\" class=\"data row195 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col1\" class=\"data row195 col1\" >96</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col2\" class=\"data row195 col2\" >22022</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col3\" class=\"data row195 col3\" >31053</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col4\" class=\"data row195 col4\" >9031</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row195_col5\" class=\"data row195 col5\" >41.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row196\" class=\"row_heading level0 row196\" >302</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col0\" class=\"data row196 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col1\" class=\"data row196 col1\" >98</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col2\" class=\"data row196 col2\" >37532</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col3\" class=\"data row196 col3\" >46208</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col4\" class=\"data row196 col4\" >8676</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row196_col5\" class=\"data row196 col5\" >23.12%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row197\" class=\"row_heading level0 row197\" >301</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col0\" class=\"data row197 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col1\" class=\"data row197 col1\" >97</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col2\" class=\"data row197 col2\" >54118</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col3\" class=\"data row197 col3\" >62779</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col4\" class=\"data row197 col4\" >8661</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row197_col5\" class=\"data row197 col5\" >16.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row198\" class=\"row_heading level0 row198\" >85</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col0\" class=\"data row198 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col1\" class=\"data row198 col1\" >85</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col2\" class=\"data row198 col2\" >915013</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col3\" class=\"data row198 col3\" >922947</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col4\" class=\"data row198 col4\" >7934</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row198_col5\" class=\"data row198 col5\" >0.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row199\" class=\"row_heading level0 row199\" >83</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col0\" class=\"data row199 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col1\" class=\"data row199 col1\" >83</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col2\" class=\"data row199 col2\" >1081440</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col3\" class=\"data row199 col3\" >1088601</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col4\" class=\"data row199 col4\" >7161</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row199_col5\" class=\"data row199 col5\" >0.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row200\" class=\"row_heading level0 row200\" >303</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col0\" class=\"data row200 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col1\" class=\"data row200 col1\" >99</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col2\" class=\"data row200 col2\" >26074</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col3\" class=\"data row200 col3\" >32517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col4\" class=\"data row200 col4\" >6443</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row200_col5\" class=\"data row200 col5\" >24.71%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row201\" class=\"row_heading level0 row201\" >199</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col0\" class=\"data row201 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col1\" class=\"data row201 col1\" >97</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col2\" class=\"data row201 col2\" >14775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col3\" class=\"data row201 col3\" >20310</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col4\" class=\"data row201 col4\" >5535</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row201_col5\" class=\"data row201 col5\" >37.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row202\" class=\"row_heading level0 row202\" >290</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col0\" class=\"data row202 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col1\" class=\"data row202 col1\" >86</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col2\" class=\"data row202 col2\" >526153</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col3\" class=\"data row202 col3\" >531680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col4\" class=\"data row202 col4\" >5527</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row202_col5\" class=\"data row202 col5\" >1.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row203\" class=\"row_heading level0 row203\" >202</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col0\" class=\"data row203 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col1\" class=\"data row203 col1\" >100</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col2\" class=\"data row203 col2\" >9352</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col3\" class=\"data row203 col3\" >13618</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col4\" class=\"data row203 col4\" >4266</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row203_col5\" class=\"data row203 col5\" >45.62%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row204\" class=\"row_heading level0 row204\" >200</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col0\" class=\"data row204 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col1\" class=\"data row204 col1\" >98</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col2\" class=\"data row204 col2\" >9505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col3\" class=\"data row204 col3\" >13518</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col4\" class=\"data row204 col4\" >4013</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row204_col5\" class=\"data row204 col5\" >42.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row205\" class=\"row_heading level0 row205\" >201</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col0\" class=\"data row205 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col1\" class=\"data row205 col1\" >99</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col2\" class=\"data row205 col2\" >6104</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col3\" class=\"data row205 col3\" >8951</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col4\" class=\"data row205 col4\" >2847</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row205_col5\" class=\"data row205 col5\" >46.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row206\" class=\"row_heading level0 row206\" >102</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col0\" class=\"data row206 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col1\" class=\"data row206 col1\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col2\" class=\"data row206 col2\" >2018420</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col3\" class=\"data row206 col3\" >2020326</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col4\" class=\"data row206 col4\" >1906</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row206_col5\" class=\"data row206 col5\" >0.09%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row207\" class=\"row_heading level0 row207\" >81</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col0\" class=\"data row207 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col1\" class=\"data row207 col1\" >81</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col2\" class=\"data row207 col2\" >1212603</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col3\" class=\"data row207 col3\" >1214357</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col4\" class=\"data row207 col4\" >1754</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row207_col5\" class=\"data row207 col5\" >0.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row208\" class=\"row_heading level0 row208\" >154</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col0\" class=\"data row208 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col1\" class=\"data row208 col1\" >52</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col2\" class=\"data row208 col2\" >2197161</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col3\" class=\"data row208 col3\" >2197801</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col4\" class=\"data row208 col4\" >640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row208_col5\" class=\"data row208 col5\" >0.03%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row209\" class=\"row_heading level0 row209\" >144</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col0\" class=\"data row209 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col1\" class=\"data row209 col1\" >42</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col2\" class=\"data row209 col2\" >2031782</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col3\" class=\"data row209 col3\" >2032207</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col4\" class=\"data row209 col4\" >425</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row209_col5\" class=\"data row209 col5\" >0.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row210\" class=\"row_heading level0 row210\" >52</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col0\" class=\"data row210 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col1\" class=\"data row210 col1\" >52</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col2\" class=\"data row210 col2\" >4480584</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col3\" class=\"data row210 col3\" >4480188</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col4\" class=\"data row210 col4\" >-396</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row210_col5\" class=\"data row210 col5\" >-0.01%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row211\" class=\"row_heading level0 row211\" >256</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col0\" class=\"data row211 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col1\" class=\"data row211 col1\" >52</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col2\" class=\"data row211 col2\" >2283423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col3\" class=\"data row211 col3\" >2282387</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col4\" class=\"data row211 col4\" >-1036</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row211_col5\" class=\"data row211 col5\" >-0.05%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row212\" class=\"row_heading level0 row212\" >0</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col0\" class=\"data row212 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col1\" class=\"data row212 col1\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col2\" class=\"data row212 col2\" >3951330</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col3\" class=\"data row212 col3\" >3949775</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col4\" class=\"data row212 col4\" >-1555</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row212_col5\" class=\"data row212 col5\" >-0.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row213\" class=\"row_heading level0 row213\" >103</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col0\" class=\"data row213 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col1\" class=\"data row213 col1\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col2\" class=\"data row213 col2\" >2020332</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col3\" class=\"data row213 col3\" >2018401</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col4\" class=\"data row213 col4\" >-1931</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row213_col5\" class=\"data row213 col5\" >-0.10%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row214\" class=\"row_heading level0 row214\" >204</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col0\" class=\"data row214 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col1\" class=\"data row214 col1\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col2\" class=\"data row214 col2\" >1932910</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col3\" class=\"data row214 col3\" >1929449</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col4\" class=\"data row214 col4\" >-3461</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row214_col5\" class=\"data row214 col5\" >-0.18%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row215\" class=\"row_heading level0 row215\" >153</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col0\" class=\"data row215 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col1\" class=\"data row215 col1\" >51</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col2\" class=\"data row215 col2\" >2209780</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col3\" class=\"data row215 col3\" >2205399</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col4\" class=\"data row215 col4\" >-4381</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row215_col5\" class=\"data row215 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row216\" class=\"row_heading level0 row216\" >255</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col0\" class=\"data row216 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col1\" class=\"data row216 col1\" >51</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col2\" class=\"data row216 col2\" >2289194</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col3\" class=\"data row216 col3\" >2283994</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col4\" class=\"data row216 col4\" >-5200</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row216_col5\" class=\"data row216 col5\" >-0.23%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row217\" class=\"row_heading level0 row217\" >205</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col0\" class=\"data row217 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col1\" class=\"data row217 col1\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col2\" class=\"data row217 col2\" >1937556</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col3\" class=\"data row217 col3\" >1931375</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col4\" class=\"data row217 col4\" >-6181</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row217_col5\" class=\"data row217 col5\" >-0.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row218\" class=\"row_heading level0 row218\" >82</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col0\" class=\"data row218 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col1\" class=\"data row218 col1\" >82</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col2\" class=\"data row218 col2\" >1158351</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col3\" class=\"data row218 col3\" >1151677</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col4\" class=\"data row218 col4\" >-6674</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row218_col5\" class=\"data row218 col5\" >-0.58%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row219\" class=\"row_heading level0 row219\" >215</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col0\" class=\"data row219 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col1\" class=\"data row219 col1\" >11</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col2\" class=\"data row219 col2\" >2010714</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col3\" class=\"data row219 col3\" >2003233</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col4\" class=\"data row219 col4\" >-7481</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row219_col5\" class=\"data row219 col5\" >-0.37%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row220\" class=\"row_heading level0 row220\" >213</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col0\" class=\"data row220 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col1\" class=\"data row220 col1\" >9</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col2\" class=\"data row220 col2\" >2018378</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col3\" class=\"data row220 col3\" >2010659</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col4\" class=\"data row220 col4\" >-7719</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row220_col5\" class=\"data row220 col5\" >-0.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row221\" class=\"row_heading level0 row221\" >1</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col0\" class=\"data row221 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col1\" class=\"data row221 col1\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col2\" class=\"data row221 col2\" >3957888</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col3\" class=\"data row221 col3\" >3949776</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col4\" class=\"data row221 col4\" >-8112</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row221_col5\" class=\"data row221 col5\" >-0.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row222\" class=\"row_heading level0 row222\" >111</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col0\" class=\"data row222 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col1\" class=\"data row222 col1\" >9</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col2\" class=\"data row222 col2\" >2107037</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col3\" class=\"data row222 col3\" >2097690</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col4\" class=\"data row222 col4\" >-9347</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row222_col5\" class=\"data row222 col5\" >-0.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row223\" class=\"row_heading level0 row223\" >51</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col0\" class=\"data row223 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col1\" class=\"data row223 col1\" >51</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col2\" class=\"data row223 col2\" >4498974</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col3\" class=\"data row223 col3\" >4489393</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col4\" class=\"data row223 col4\" >-9581</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row223_col5\" class=\"data row223 col5\" >-0.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row224\" class=\"row_heading level0 row224\" >182</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col0\" class=\"data row224 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col1\" class=\"data row224 col1\" >80</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col2\" class=\"data row224 col2\" >549216</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col3\" class=\"data row224 col3\" >539227</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col4\" class=\"data row224 col4\" >-9989</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row224_col5\" class=\"data row224 col5\" >-1.82%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row225\" class=\"row_heading level0 row225\" >287</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col0\" class=\"data row225 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col1\" class=\"data row225 col1\" >83</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col2\" class=\"data row225 col2\" >658441</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col3\" class=\"data row225 col3\" >647071</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col4\" class=\"data row225 col4\" >-11370</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row225_col5\" class=\"data row225 col5\" >-1.73%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row226\" class=\"row_heading level0 row226\" >285</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col0\" class=\"data row226 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col1\" class=\"data row226 col1\" >81</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col2\" class=\"data row226 col2\" >716533</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col3\" class=\"data row226 col3\" >704052</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col4\" class=\"data row226 col4\" >-12481</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row226_col5\" class=\"data row226 col5\" >-1.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row227\" class=\"row_heading level0 row227\" >289</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col0\" class=\"data row227 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col1\" class=\"data row227 col1\" >85</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col2\" class=\"data row227 col2\" >577352</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col3\" class=\"data row227 col3\" >564605</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col4\" class=\"data row227 col4\" >-12747</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row227_col5\" class=\"data row227 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row228\" class=\"row_heading level0 row228\" >216</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col0\" class=\"data row228 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col1\" class=\"data row228 col1\" >12</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col2\" class=\"data row228 col2\" >2009630</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col3\" class=\"data row228 col3\" >1994846</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col4\" class=\"data row228 col4\" >-14784</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row228_col5\" class=\"data row228 col5\" >-0.74%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row229\" class=\"row_heading level0 row229\" >9</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col0\" class=\"data row229 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col1\" class=\"data row229 col1\" >9</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col2\" class=\"data row229 col2\" >4125415</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col3\" class=\"data row229 col3\" >4108349</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col4\" class=\"data row229 col4\" >-17066</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row229_col5\" class=\"data row229 col5\" >-0.41%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row230\" class=\"row_heading level0 row230\" >286</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col0\" class=\"data row230 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col1\" class=\"data row230 col1\" >82</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col2\" class=\"data row230 col2\" >695544</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col3\" class=\"data row230 col3\" >675643</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col4\" class=\"data row230 col4\" >-19901</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row230_col5\" class=\"data row230 col5\" >-2.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row231\" class=\"row_heading level0 row231\" >113</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col0\" class=\"data row231 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col1\" class=\"data row231 col1\" >11</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col2\" class=\"data row231 col2\" >2104797</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col3\" class=\"data row231 col3\" >2084169</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col4\" class=\"data row231 col4\" >-20628</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row231_col5\" class=\"data row231 col5\" >-0.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row232\" class=\"row_heading level0 row232\" >234</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col0\" class=\"data row232 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col1\" class=\"data row232 col1\" >30</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col2\" class=\"data row232 col2\" >2136744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col3\" class=\"data row232 col3\" >2113094</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col4\" class=\"data row232 col4\" >-23650</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row232_col5\" class=\"data row232 col5\" >-1.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row233\" class=\"row_heading level0 row233\" >219</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col0\" class=\"data row233 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col1\" class=\"data row233 col1\" >15</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col2\" class=\"data row233 col2\" >2060560</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col3\" class=\"data row233 col3\" >2035734</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col4\" class=\"data row233 col4\" >-24826</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row233_col5\" class=\"data row233 col5\" >-1.20%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row234\" class=\"row_heading level0 row234\" >132</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col0\" class=\"data row234 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col1\" class=\"data row234 col1\" >30</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col2\" class=\"data row234 col2\" >2167495</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col3\" class=\"data row234 col3\" >2142240</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col4\" class=\"data row234 col4\" >-25255</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row234_col5\" class=\"data row234 col5\" >-1.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row235\" class=\"row_heading level0 row235\" >209</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col0\" class=\"data row235 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col1\" class=\"data row235 col1\" >5</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col2\" class=\"data row235 col2\" >1988080</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col3\" class=\"data row235 col3\" >1962561</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col4\" class=\"data row235 col4\" >-25519</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row235_col5\" class=\"data row235 col5\" >-1.28%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row236\" class=\"row_heading level0 row236\" >267</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col0\" class=\"data row236 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col1\" class=\"data row236 col1\" >63</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col2\" class=\"data row236 col2\" >1898264</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col3\" class=\"data row236 col3\" >1870596</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col4\" class=\"data row236 col4\" >-27668</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row236_col5\" class=\"data row236 col5\" >-1.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row237\" class=\"row_heading level0 row237\" >114</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col0\" class=\"data row237 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col1\" class=\"data row237 col1\" >12</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col2\" class=\"data row237 col2\" >2103649</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col3\" class=\"data row237 col3\" >2075836</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col4\" class=\"data row237 col4\" >-27813</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row237_col5\" class=\"data row237 col5\" >-1.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row238\" class=\"row_heading level0 row238\" >11</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col0\" class=\"data row238 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col1\" class=\"data row238 col1\" >11</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col2\" class=\"data row238 col2\" >4115511</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col3\" class=\"data row238 col3\" >4087402</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col4\" class=\"data row238 col4\" >-28109</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row238_col5\" class=\"data row238 col5\" >-0.68%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row239\" class=\"row_heading level0 row239\" >214</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col0\" class=\"data row239 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col1\" class=\"data row239 col1\" >10</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col2\" class=\"data row239 col2\" >2044895</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col3\" class=\"data row239 col3\" >2016680</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col4\" class=\"data row239 col4\" >-28215</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row239_col5\" class=\"data row239 col5\" >-1.38%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row240\" class=\"row_heading level0 row240\" >208</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col0\" class=\"data row240 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col1\" class=\"data row240 col1\" >4</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col2\" class=\"data row240 col2\" >1993239</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col3\" class=\"data row240 col3\" >1961199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col4\" class=\"data row240 col4\" >-32040</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row240_col5\" class=\"data row240 col5\" >-1.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row241\" class=\"row_heading level0 row241\" >107</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col0\" class=\"data row241 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col1\" class=\"data row241 col1\" >5</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col2\" class=\"data row241 col2\" >2076573</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col3\" class=\"data row241 col3\" >2044339</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col4\" class=\"data row241 col4\" >-32234</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row241_col5\" class=\"data row241 col5\" >-1.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row242\" class=\"row_heading level0 row242\" >106</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col0\" class=\"data row242 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col1\" class=\"data row242 col1\" >4</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col2\" class=\"data row242 col2\" >2084312</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col3\" class=\"data row242 col3\" >2044517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col4\" class=\"data row242 col4\" >-39795</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row242_col5\" class=\"data row242 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row243\" class=\"row_heading level0 row243\" >117</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col0\" class=\"data row243 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col1\" class=\"data row243 col1\" >15</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col2\" class=\"data row243 col2\" >2170442</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col3\" class=\"data row243 col3\" >2129062</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col4\" class=\"data row243 col4\" >-41380</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row243_col5\" class=\"data row243 col5\" >-1.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row244\" class=\"row_heading level0 row244\" >112</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col0\" class=\"data row244 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col1\" class=\"data row244 col1\" >10</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col2\" class=\"data row244 col2\" >2142167</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col3\" class=\"data row244 col3\" >2100262</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col4\" class=\"data row244 col4\" >-41905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row244_col5\" class=\"data row244 col5\" >-1.96%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row245\" class=\"row_heading level0 row245\" >12</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col0\" class=\"data row245 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col1\" class=\"data row245 col1\" >12</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col2\" class=\"data row245 col2\" >4113279</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col3\" class=\"data row245 col3\" >4070682</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col4\" class=\"data row245 col4\" >-42597</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row245_col5\" class=\"data row245 col5\" >-1.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row246\" class=\"row_heading level0 row246\" >284</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col0\" class=\"data row246 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col1\" class=\"data row246 col1\" >80</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col2\" class=\"data row246 col2\" >770509</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col3\" class=\"data row246 col3\" >723310</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col4\" class=\"data row246 col4\" >-47199</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row246_col5\" class=\"data row246 col5\" >-6.13%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row247\" class=\"row_heading level0 row247\" >30</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col0\" class=\"data row247 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col1\" class=\"data row247 col1\" >30</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col2\" class=\"data row247 col2\" >4304239</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col3\" class=\"data row247 col3\" >4255334</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col4\" class=\"data row247 col4\" >-48905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row247_col5\" class=\"data row247 col5\" >-1.14%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row248\" class=\"row_heading level0 row248\" >105</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col0\" class=\"data row248 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col1\" class=\"data row248 col1\" >3</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col2\" class=\"data row248 col2\" >2101272</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col3\" class=\"data row248 col3\" >2049596</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col4\" class=\"data row248 col4\" >-51676</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row248_col5\" class=\"data row248 col5\" >-2.46%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row249\" class=\"row_heading level0 row249\" >165</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col0\" class=\"data row249 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col1\" class=\"data row249 col1\" >63</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col2\" class=\"data row249 col2\" >1753903</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col3\" class=\"data row249 col3\" >1701014</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col4\" class=\"data row249 col4\" >-52889</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row249_col5\" class=\"data row249 col5\" >-3.02%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row250\" class=\"row_heading level0 row250\" >207</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col0\" class=\"data row250 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col1\" class=\"data row250 col1\" >3</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col2\" class=\"data row250 col2\" >2010648</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col3\" class=\"data row250 col3\" >1957483</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col4\" class=\"data row250 col4\" >-53165</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row250_col5\" class=\"data row250 col5\" >-2.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row251\" class=\"row_heading level0 row251\" >80</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col0\" class=\"data row251 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col1\" class=\"data row251 col1\" >80</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col2\" class=\"data row251 col2\" >1319725</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col3\" class=\"data row251 col3\" >1262537</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col4\" class=\"data row251 col4\" >-57188</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row251_col5\" class=\"data row251 col5\" >-4.33%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row252\" class=\"row_heading level0 row252\" >5</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col0\" class=\"data row252 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col1\" class=\"data row252 col1\" >5</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col2\" class=\"data row252 col2\" >4064653</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col3\" class=\"data row252 col3\" >4006900</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col4\" class=\"data row252 col4\" >-57753</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row252_col5\" class=\"data row252 col5\" >-1.42%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row253\" class=\"row_heading level0 row253\" >122</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col0\" class=\"data row253 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col1\" class=\"data row253 col1\" >20</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col2\" class=\"data row253 col2\" >2331845</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col3\" class=\"data row253 col3\" >2271216</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col4\" class=\"data row253 col4\" >-60629</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row253_col5\" class=\"data row253 col5\" >-2.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row254\" class=\"row_heading level0 row254\" >220</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col0\" class=\"data row254 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col1\" class=\"data row254 col1\" >16</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col2\" class=\"data row254 col2\" >2098220</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col3\" class=\"data row254 col3\" >2037134</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col4\" class=\"data row254 col4\" >-61086</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row254_col5\" class=\"data row254 col5\" >-2.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row255\" class=\"row_heading level0 row255\" >104</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col0\" class=\"data row255 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col1\" class=\"data row255 col1\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col2\" class=\"data row255 col2\" >2088685</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col3\" class=\"data row255 col3\" >2023673</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col4\" class=\"data row255 col4\" >-65012</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row255_col5\" class=\"data row255 col5\" >-3.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row256\" class=\"row_heading level0 row256\" >206</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col0\" class=\"data row256 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col1\" class=\"data row256 col1\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col2\" class=\"data row256 col2\" >2002177</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col3\" class=\"data row256 col3\" >1935991</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col4\" class=\"data row256 col4\" >-66186</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row256_col5\" class=\"data row256 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row257\" class=\"row_heading level0 row257\" >15</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col0\" class=\"data row257 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col1\" class=\"data row257 col1\" >15</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col2\" class=\"data row257 col2\" >4231002</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col3\" class=\"data row257 col3\" >4164796</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col4\" class=\"data row257 col4\" >-66206</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row257_col5\" class=\"data row257 col5\" >-1.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row258\" class=\"row_heading level0 row258\" >10</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col0\" class=\"data row258 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col1\" class=\"data row258 col1\" >10</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col2\" class=\"data row258 col2\" >4187062</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col3\" class=\"data row258 col3\" >4116942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col4\" class=\"data row258 col4\" >-70120</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row258_col5\" class=\"data row258 col5\" >-1.67%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row259\" class=\"row_heading level0 row259\" >4</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col0\" class=\"data row259 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col1\" class=\"data row259 col1\" >4</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col2\" class=\"data row259 col2\" >4077551</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col3\" class=\"data row259 col3\" >4005716</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col4\" class=\"data row259 col4\" >-71835</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row259_col5\" class=\"data row259 col5\" >-1.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row260\" class=\"row_heading level0 row260\" >254</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col0\" class=\"data row260 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col1\" class=\"data row260 col1\" >50</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col2\" class=\"data row260 col2\" >2355369</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col3\" class=\"data row260 col3\" >2280640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col4\" class=\"data row260 col4\" >-74729</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row260_col5\" class=\"data row260 col5\" >-3.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row261\" class=\"row_heading level0 row261\" >221</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col0\" class=\"data row261 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col1\" class=\"data row261 col1\" >17</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col2\" class=\"data row261 col2\" >2123529</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col3\" class=\"data row261 col3\" >2047152</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col4\" class=\"data row261 col4\" >-76377</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row261_col5\" class=\"data row261 col5\" >-3.60%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row262\" class=\"row_heading level0 row262\" >152</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col0\" class=\"data row262 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col1\" class=\"data row262 col1\" >50</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col2\" class=\"data row262 col2\" >2290862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col3\" class=\"data row262 col3\" >2211767</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col4\" class=\"data row262 col4\" >-79095</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row262_col5\" class=\"data row262 col5\" >-3.45%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row263\" class=\"row_heading level0 row263\" >63</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col0\" class=\"data row263 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col1\" class=\"data row263 col1\" >63</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col2\" class=\"data row263 col2\" >3652167</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col3\" class=\"data row263 col3\" >3571610</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col4\" class=\"data row263 col4\" >-80557</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row263_col5\" class=\"data row263 col5\" >-2.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row264\" class=\"row_heading level0 row264\" >151</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col0\" class=\"data row264 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col1\" class=\"data row264 col1\" >49</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col2\" class=\"data row264 col2\" >2262458</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col3\" class=\"data row264 col3\" >2180214</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col4\" class=\"data row264 col4\" >-82244</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row264_col5\" class=\"data row264 col5\" >-3.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row265\" class=\"row_heading level0 row265\" >118</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col0\" class=\"data row265 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col1\" class=\"data row265 col1\" >16</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col2\" class=\"data row265 col2\" >2215032</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col3\" class=\"data row265 col3\" >2131425</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col4\" class=\"data row265 col4\" >-83607</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row265_col5\" class=\"data row265 col5\" >-3.77%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row266\" class=\"row_heading level0 row266\" >224</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col0\" class=\"data row266 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col1\" class=\"data row266 col1\" >20</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col2\" class=\"data row266 col2\" >2236672</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col3\" class=\"data row266 col3\" >2150114</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col4\" class=\"data row266 col4\" >-86558</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row266_col5\" class=\"data row266 col5\" >-3.87%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row267\" class=\"row_heading level0 row267\" >3</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col0\" class=\"data row267 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col1\" class=\"data row267 col1\" >3</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col2\" class=\"data row267 col2\" >4111920</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col3\" class=\"data row267 col3\" >4007079</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col4\" class=\"data row267 col4\" >-104841</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row267_col5\" class=\"data row267 col5\" >-2.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row268\" class=\"row_heading level0 row268\" >140</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col0\" class=\"data row268 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col1\" class=\"data row268 col1\" >38</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col2\" class=\"data row268 col2\" >2028052</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col3\" class=\"data row268 col3\" >1923133</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col4\" class=\"data row268 col4\" >-104919</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row268_col5\" class=\"data row268 col5\" >-5.17%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row269\" class=\"row_heading level0 row269\" >253</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col0\" class=\"data row269 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col1\" class=\"data row269 col1\" >49</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col2\" class=\"data row269 col2\" >2336640</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col3\" class=\"data row269 col3\" >2230032</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col4\" class=\"data row269 col4\" >-106608</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row269_col5\" class=\"data row269 col5\" >-4.56%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row270\" class=\"row_heading level0 row270\" >245</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col0\" class=\"data row270 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col1\" class=\"data row270 col1\" >41</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col2\" class=\"data row270 col2\" >2089576</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col3\" class=\"data row270 col3\" >1978607</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col4\" class=\"data row270 col4\" >-110969</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row270_col5\" class=\"data row270 col5\" >-5.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row271\" class=\"row_heading level0 row271\" >121</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col0\" class=\"data row271 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col1\" class=\"data row271 col1\" >19</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col2\" class=\"data row271 col2\" >2334906</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col3\" class=\"data row271 col3\" >2221910</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col4\" class=\"data row271 col4\" >-112996</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row271_col5\" class=\"data row271 col5\" >-4.84%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row272\" class=\"row_heading level0 row272\" >119</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col0\" class=\"data row272 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col1\" class=\"data row272 col1\" >17</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col2\" class=\"data row272 col2\" >2252838</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col3\" class=\"data row272 col3\" >2139361</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col4\" class=\"data row272 col4\" >-113477</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row272_col5\" class=\"data row272 col5\" >-5.04%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row273\" class=\"row_heading level0 row273\" >242</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col0\" class=\"data row273 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col1\" class=\"data row273 col1\" >38</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col2\" class=\"data row273 col2\" >2052176</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col3\" class=\"data row273 col3\" >1938503</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col4\" class=\"data row273 col4\" >-113673</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row273_col5\" class=\"data row273 col5\" >-5.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row274\" class=\"row_heading level0 row274\" >222</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col0\" class=\"data row274 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col1\" class=\"data row274 col1\" >18</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col2\" class=\"data row274 col2\" >2185272</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col3\" class=\"data row274 col3\" >2062176</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col4\" class=\"data row274 col4\" >-123096</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row274_col5\" class=\"data row274 col5\" >-5.63%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row275\" class=\"row_heading level0 row275\" >223</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col0\" class=\"data row275 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col1\" class=\"data row275 col1\" >19</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col2\" class=\"data row275 col2\" >2236505</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col3\" class=\"data row275 col3\" >2107128</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col4\" class=\"data row275 col4\" >-129377</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row275_col5\" class=\"data row275 col5\" >-5.78%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row276\" class=\"row_heading level0 row276\" >2</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col0\" class=\"data row276 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col1\" class=\"data row276 col1\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col2\" class=\"data row276 col2\" >4090862</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col3\" class=\"data row276 col3\" >3959664</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col4\" class=\"data row276 col4\" >-131198</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row276_col5\" class=\"data row276 col5\" >-3.21%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row277\" class=\"row_heading level0 row277\" >143</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col0\" class=\"data row277 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col1\" class=\"data row277 col1\" >41</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col2\" class=\"data row277 col2\" >2073902</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col3\" class=\"data row277 col3\" >1941203</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col4\" class=\"data row277 col4\" >-132699</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row277_col5\" class=\"data row277 col5\" >-6.40%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row278\" class=\"row_heading level0 row278\" >147</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col0\" class=\"data row278 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col1\" class=\"data row278 col1\" >45</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col2\" class=\"data row278 col2\" >2201905</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col3\" class=\"data row278 col3\" >2067426</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col4\" class=\"data row278 col4\" >-134479</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row278_col5\" class=\"data row278 col5\" >-6.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row279\" class=\"row_heading level0 row279\" >120</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col0\" class=\"data row279 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col1\" class=\"data row279 col1\" >18</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col2\" class=\"data row279 col2\" >2305733</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col3\" class=\"data row279 col3\" >2165744</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col4\" class=\"data row279 col4\" >-139989</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row279_col5\" class=\"data row279 col5\" >-6.07%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row280\" class=\"row_heading level0 row280\" >249</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col0\" class=\"data row280 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col1\" class=\"data row280 col1\" >45</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col2\" class=\"data row280 col2\" >2236654</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col3\" class=\"data row280 col3\" >2095203</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col4\" class=\"data row280 col4\" >-141451</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row280_col5\" class=\"data row280 col5\" >-6.32%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row281\" class=\"row_heading level0 row281\" >16</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col0\" class=\"data row281 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col1\" class=\"data row281 col1\" >16</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col2\" class=\"data row281 col2\" >4313252</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col3\" class=\"data row281 col3\" >4168559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col4\" class=\"data row281 col4\" >-144693</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row281_col5\" class=\"data row281 col5\" >-3.35%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row282\" class=\"row_heading level0 row282\" >20</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col0\" class=\"data row282 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col1\" class=\"data row282 col1\" >20</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col2\" class=\"data row282 col2\" >4568517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col3\" class=\"data row282 col3\" >4421330</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col4\" class=\"data row282 col4\" >-147187</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row282_col5\" class=\"data row282 col5\" >-3.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row283\" class=\"row_heading level0 row283\" >50</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col0\" class=\"data row283 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col1\" class=\"data row283 col1\" >50</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col2\" class=\"data row283 col2\" >4646231</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col3\" class=\"data row283 col3\" >4492407</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col4\" class=\"data row283 col4\" >-153824</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row283_col5\" class=\"data row283 col5\" >-3.31%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row284\" class=\"row_heading level0 row284\" >141</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col0\" class=\"data row284 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col1\" class=\"data row284 col1\" >39</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col2\" class=\"data row284 col2\" >2148718</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col3\" class=\"data row284 col3\" >1986712</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col4\" class=\"data row284 col4\" >-162006</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row284_col5\" class=\"data row284 col5\" >-7.54%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row285\" class=\"row_heading level0 row285\" >150</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col0\" class=\"data row285 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col1\" class=\"data row285 col1\" >48</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col2\" class=\"data row285 col2\" >2235296</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col3\" class=\"data row285 col3\" >2058392</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col4\" class=\"data row285 col4\" >-176904</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row285_col5\" class=\"data row285 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row286\" class=\"row_heading level0 row286\" >243</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col0\" class=\"data row286 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col1\" class=\"data row286 col1\" >39</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col2\" class=\"data row286 col2\" >2175745</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col3\" class=\"data row286 col3\" >1995795</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col4\" class=\"data row286 col4\" >-179950</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row286_col5\" class=\"data row286 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row287\" class=\"row_heading level0 row287\" >49</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col0\" class=\"data row287 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col1\" class=\"data row287 col1\" >49</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col2\" class=\"data row287 col2\" >4599098</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col3\" class=\"data row287 col3\" >4410246</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col4\" class=\"data row287 col4\" >-188852</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row287_col5\" class=\"data row287 col5\" >-4.11%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row288\" class=\"row_heading level0 row288\" >17</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col0\" class=\"data row288 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col1\" class=\"data row288 col1\" >17</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col2\" class=\"data row288 col2\" >4376367</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col3\" class=\"data row288 col3\" >4186513</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col4\" class=\"data row288 col4\" >-189854</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row288_col5\" class=\"data row288 col5\" >-4.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row289\" class=\"row_heading level0 row289\" >252</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col0\" class=\"data row289 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col1\" class=\"data row289 col1\" >48</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col2\" class=\"data row289 col2\" >2299367</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col3\" class=\"data row289 col3\" >2101346</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col4\" class=\"data row289 col4\" >-198021</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row289_col5\" class=\"data row289 col5\" >-8.61%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row290\" class=\"row_heading level0 row290\" >148</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col0\" class=\"data row290 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col1\" class=\"data row290 col1\" >46</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col2\" class=\"data row290 col2\" >2238774</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col3\" class=\"data row290 col3\" >2023033</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col4\" class=\"data row290 col4\" >-215741</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row290_col5\" class=\"data row290 col5\" >-9.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row291\" class=\"row_heading level0 row291\" >149</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col0\" class=\"data row291 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col1\" class=\"data row291 col1\" >47</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col2\" class=\"data row291 col2\" >2237940</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col3\" class=\"data row291 col3\" >2019517</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col4\" class=\"data row291 col4\" >-218423</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row291_col5\" class=\"data row291 col5\" >-9.76%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row292\" class=\"row_heading level0 row292\" >38</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col0\" class=\"data row292 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col1\" class=\"data row292 col1\" >38</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col2\" class=\"data row292 col2\" >4080228</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col3\" class=\"data row292 col3\" >3861636</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col4\" class=\"data row292 col4\" >-218592</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row292_col5\" class=\"data row292 col5\" >-5.36%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row293\" class=\"row_heading level0 row293\" >251</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col0\" class=\"data row293 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col1\" class=\"data row293 col1\" >47</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col2\" class=\"data row293 col2\" >2297533</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col3\" class=\"data row293 col3\" >2063366</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col4\" class=\"data row293 col4\" >-234167</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row293_col5\" class=\"data row293 col5\" >-10.19%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row294\" class=\"row_heading level0 row294\" >250</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col0\" class=\"data row294 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col1\" class=\"data row294 col1\" >46</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col2\" class=\"data row294 col2\" >2290942</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col3\" class=\"data row294 col3\" >2054118</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col4\" class=\"data row294 col4\" >-236824</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row294_col5\" class=\"data row294 col5\" >-10.34%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row295\" class=\"row_heading level0 row295\" >19</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col0\" class=\"data row295 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col1\" class=\"data row295 col1\" >19</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col2\" class=\"data row295 col2\" >4571411</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col3\" class=\"data row295 col3\" >4329038</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col4\" class=\"data row295 col4\" >-242373</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row295_col5\" class=\"data row295 col5\" >-5.30%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row296\" class=\"row_heading level0 row296\" >41</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col0\" class=\"data row296 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col1\" class=\"data row296 col1\" >41</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col2\" class=\"data row296 col2\" >4163478</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col3\" class=\"data row296 col3\" >3919810</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col4\" class=\"data row296 col4\" >-243668</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row296_col5\" class=\"data row296 col5\" >-5.85%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row297\" class=\"row_heading level0 row297\" >244</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col0\" class=\"data row297 col0\" >2</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col1\" class=\"data row297 col1\" >40</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col2\" class=\"data row297 col2\" >2197964</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col3\" class=\"data row297 col3\" >1942194</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col4\" class=\"data row297 col4\" >-255770</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row297_col5\" class=\"data row297 col5\" >-11.64%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row298\" class=\"row_heading level0 row298\" >18</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col0\" class=\"data row298 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col1\" class=\"data row298 col1\" >18</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col2\" class=\"data row298 col2\" >4491005</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col3\" class=\"data row298 col3\" >4227920</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col4\" class=\"data row298 col4\" >-263085</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row298_col5\" class=\"data row298 col5\" >-5.86%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row299\" class=\"row_heading level0 row299\" >142</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col0\" class=\"data row299 col0\" >1</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col1\" class=\"data row299 col1\" >40</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col2\" class=\"data row299 col2\" >2189516</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col3\" class=\"data row299 col3\" >1917201</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col4\" class=\"data row299 col4\" >-272315</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row299_col5\" class=\"data row299 col5\" >-12.44%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row300\" class=\"row_heading level0 row300\" >45</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col0\" class=\"data row300 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col1\" class=\"data row300 col1\" >45</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col2\" class=\"data row300 col2\" >4438559</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col3\" class=\"data row300 col3\" >4162629</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col4\" class=\"data row300 col4\" >-275930</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row300_col5\" class=\"data row300 col5\" >-6.22%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row301\" class=\"row_heading level0 row301\" >39</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col0\" class=\"data row301 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col1\" class=\"data row301 col1\" >39</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col2\" class=\"data row301 col2\" >4324463</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col3\" class=\"data row301 col3\" >3982507</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col4\" class=\"data row301 col4\" >-341956</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row301_col5\" class=\"data row301 col5\" >-7.91%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row302\" class=\"row_heading level0 row302\" >48</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col0\" class=\"data row302 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col1\" class=\"data row302 col1\" >48</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col2\" class=\"data row302 col2\" >4534663</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col3\" class=\"data row302 col3\" >4159738</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col4\" class=\"data row302 col4\" >-374925</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row302_col5\" class=\"data row302 col5\" >-8.27%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row303\" class=\"row_heading level0 row303\" >46</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col0\" class=\"data row303 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col1\" class=\"data row303 col1\" >46</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col2\" class=\"data row303 col2\" >4529716</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col3\" class=\"data row303 col3\" >4077151</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col4\" class=\"data row303 col4\" >-452565</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row303_col5\" class=\"data row303 col5\" >-9.99%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row304\" class=\"row_heading level0 row304\" >47</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col0\" class=\"data row304 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col1\" class=\"data row304 col1\" >47</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col2\" class=\"data row304 col2\" >4535473</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col3\" class=\"data row304 col3\" >4082883</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col4\" class=\"data row304 col4\" >-452590</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row304_col5\" class=\"data row304 col5\" >-9.98%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_3daade6a_5280_11eb_8c0f_acde48001122level0_row305\" class=\"row_heading level0 row305\" >40</th>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col0\" class=\"data row305 col0\" >0</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col1\" class=\"data row305 col1\" >40</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col2\" class=\"data row305 col2\" >4387480</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col3\" class=\"data row305 col3\" >3859395</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col4\" class=\"data row305 col4\" >-528085</td>\n",
+       "                        <td id=\"T_3daade6a_5280_11eb_8c0f_acde48001122row305_col5\" class=\"data row305 col5\" >-12.04%</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fd9c3fc23d0>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "census.sort_values('Change', ascending=False).style.format({'Percent Change': \"{:,.2%}\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Not surprisingly, the top row of the sorted table is the line that corresponds to the entire population: both sexes and all age groups. From 2010 to 2014, the population of the United States increased by about 9.5 million people, a change of just over 3%.\n",
+    "\n",
+    "The next two rows correspond to all the men and all the women respectively. The male population grew more than the female population, both in absolute and percentage terms. Both percent changes were around 3%.\n",
+    "\n",
+    "Now take a look at the next few rows. The percent change jumps from about 3% for the overall population to almost 30% for the people in their late sixties and early seventies. This stunning change contributes to what is known as the greying of America.\n",
+    "\n",
+    "By far the greatest absolute change was among those in the 64-67 agegroup in 2014. What could explain this large increase? We can explore this question by examining the years in which the relevant groups were born.\n",
+    "\n",
+    "- Those who were in the 64-67 age group in 2010 were born in the years 1943 to 1946. The attack on Pearl Harbor was in late 1941, and by 1942 U.S. forces were heavily engaged in a massive war that ended in 1945. \n",
+    "\n",
+    "- Those who were 64 to 67 years old in 2014 were born in the years 1947 to 1950, at the height of the post-WWII baby boom in the United States. \n",
+    "\n",
+    "The post-war jump in births is the major reason for the large changes that we have observed."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

06/Tables.ipynb

@@ -0,0 +1,2286 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 6. DataFrames\n",
+    "\n",
+    "DataFrames (df's) are a fundamental object type for representing data sets. A df can be viewed in two ways:\n",
+    "* a sequence of named columns that each describe a single aspect of all entries in a data set, or\n",
+    "* a sequence of rows that each contain all information about a single entry in a data set.\n",
+    "\n",
+    "In order to use a DataFrame, import all of the module called `pandas`, by convention this is usually imported and as `pd`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Empty tables can be created using the `pd.DataFrame()` function. An empty table is usefuly because it can be extended to contain new rows and columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>A</th>\n",
+       "      <th>B</th>\n",
+       "      <th>C</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   A  B  C\n",
+       "0  0  0  0\n",
+       "1  0  0  0\n",
+       "2  0  0  0\n",
+       "3  0  0  0\n",
+       "4  0  0  0"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DataFrame(columns=['A', 'B', 'C'], index=(0,1,2,3,4)).fillna(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A dictionary is used to construct a new table with labeled columns. Each column of a df is an array.\n",
+    "\n",
+    "Below, we begin each example with an empty table that has no columns.  \n",
+    "\n",
+    "Notice:  \n",
+    "- the column heading is supplied as a `key` with the corresponding column content added as a`value` in a `{key:value}` dictionary\n",
+    "- when using a list as a data source for the `np.array()` function the list must be placed within square or `hard` brackets.  \n",
+    "- an `index` has been added automatically"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Number of petals</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Number of petals\n",
+       "0                 8\n",
+       "1                34\n",
+       "2                 5"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DataFrame({'Number of petals': np.array([8, 34, 5])})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To add two (or more) new columns, provide the label and array for each column. All columns must have the same length, or an error will occur."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Number of petals</th>\n",
+       "      <th>Name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>lotus</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "      <td>sunflower</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>rose</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Number of petals       Name\n",
+       "0                 8      lotus\n",
+       "1                34  sunflower\n",
+       "2                 5       rose"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.DataFrame({\n",
+    "    'Number of petals': np.array([8, 34, 5]),\n",
+    "    'Name':np.array(['lotus', 'sunflower', 'rose'])\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can give this table a name, and then extend the table with another column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Number of petals</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Color</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>lotus</td>\n",
+       "      <td>{pink, yellow, red}</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "      <td>sunflower</td>\n",
+       "      <td>{pink, yellow, red}</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>rose</td>\n",
+       "      <td>{pink, yellow, red}</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Number of petals       Name                Color\n",
+       "0                 8      lotus  {pink, yellow, red}\n",
+       "1                34  sunflower  {pink, yellow, red}\n",
+       "2                 5       rose  {pink, yellow, red}"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "flowers = pd.DataFrame({'Number of petals':np.array([8, 34, 5]),'Name':np.array(['lotus', 'sunflower', 'rose'])})\n",
+    "\n",
+    "flowers_two_col = flowers.copy()\n",
+    "\n",
+    "flowers['Color'] = np.array({'pink', 'yellow', 'red'})\n",
+    "\n",
+    "    \n",
+    "flowers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When a new column is added to a Dataframe a new DatFrame is **not** created, so the original DataFrame is affected. For example, the original DatFrame `flowers` before the third was added."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Number of petals</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Color</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>lotus</td>\n",
+       "      <td>{pink, yellow, red}</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "      <td>sunflower</td>\n",
+       "      <td>{pink, yellow, red}</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>rose</td>\n",
+       "      <td>{pink, yellow, red}</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Number of petals       Name                Color\n",
+       "0                 8      lotus  {pink, yellow, red}\n",
+       "1                34  sunflower  {pink, yellow, red}\n",
+       "2                 5       rose  {pink, yellow, red}"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "flowers"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Before** adding a third column a copy of df 'flowers' is created, in this case the new df created is called flowers_two_col. 'flowers_two_col = flowers`.copy()`'\n",
+    "\n",
+    "[Pandas  'df.copy()'](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.copy.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Number of petals</th>\n",
+       "      <th>Name</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>8</td>\n",
+       "      <td>lotus</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>34</td>\n",
+       "      <td>sunflower</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5</td>\n",
+       "      <td>rose</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Number of petals       Name\n",
+       "0                 8      lotus\n",
+       "1                34  sunflower\n",
+       "2                 5       rose"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "flowers_two_col"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Creating dfs in this way involves a lot of typing. If the data have already been entered somewhere, it is usually possible to use Python to read it into a table, instead of typing it all in cell by cell.\n",
+    "\n",
+    "Often, dfs are created from files that contain comma-separated values. Such files are called CSV files.\n",
+    "\n",
+    "Below, we use the Table method `pd.read_csv()` to read a CSV file that contains some of the data used by Minard in his graphic about Napoleon's Russian campaign. The data are placed in a df named `minard`.\n",
+    "\n",
+    "[pd.read_csv()](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Direction</th>\n",
+       "      <th>Survivors</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>145000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>140000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>127100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>55000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>24000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>20000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>12000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude         City Direction  Survivors\n",
+       "0       32.0      54.8     Smolensk   Advance     145000\n",
+       "1       33.2      54.9  Dorogobouge   Advance     140000\n",
+       "2       34.4      55.5        Chjat   Advance     127100\n",
+       "3       37.6      55.8       Moscou   Advance     100000\n",
+       "4       34.3      55.2        Wixma   Retreat      55000\n",
+       "5       32.0      54.6     Smolensk   Retreat      24000\n",
+       "6       30.4      54.4       Orscha   Retreat      20000\n",
+       "7       26.8      54.3    Moiodexno   Retreat      12000"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard = pd.read_csv(path_data + 'minard.csv')\n",
+    "minard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will use this small df to demonstrate some useful DataFrame methods. We will then use those same methods, and develop other methods, on much larger DataFrames."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## The Size of the Table\n",
+    "The method `df.shape(1)` gives the number of columns in the table, and `df.shape(0)` the number of rows.\n",
+    "\n",
+    "[df.shape[]](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.shape.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8, 5)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.shape[1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.shape[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### len( )\n",
+    "The number of rows in a df can also be found by using the `len()` function. For number of rows `len(df.rows)`, and number of columns `len(df.columns)`. As the default parameter for the `len()` function is set for number of rows and if we want to know the number of rows we don't usually add '.rows' "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "5"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(minard.columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "8"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(minard)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Column Labels\n",
+    "\n",
+    "The method `.columns` can be used to list the labels of all the columns. With `minard` we don't gain much by this, but it can be very useful for tables that are so large that not all columns are visible on the screen."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['Longitude', 'Latitude', 'City', 'Direction', 'Survivors'], dtype='object')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.columns"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can change column labels using the `rename(columns={})` method. This creates a **new** df and leaves `minard` unchanged."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>City Name</th>\n",
+       "      <th>Direction</th>\n",
+       "      <th>Survivors</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>145000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>140000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>127100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>55000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>24000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>20000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>12000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude    City Name Direction  Survivors\n",
+       "0       32.0      54.8     Smolensk   Advance     145000\n",
+       "1       33.2      54.9  Dorogobouge   Advance     140000\n",
+       "2       34.4      55.5        Chjat   Advance     127100\n",
+       "3       37.6      55.8       Moscou   Advance     100000\n",
+       "4       34.3      55.2        Wixma   Retreat      55000\n",
+       "5       32.0      54.6     Smolensk   Retreat      24000\n",
+       "6       30.4      54.4       Orscha   Retreat      20000\n",
+       "7       26.8      54.3    Moiodexno   Retreat      12000"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.rename(columns={'City':'City Name'})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "However, this method does not change the original DataFrame. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>City</th>\n",
+       "      <th>Direction</th>\n",
+       "      <th>Survivors</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>145000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>140000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>127100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>55000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>24000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>20000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>12000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude         City Direction  Survivors\n",
+       "0       32.0      54.8     Smolensk   Advance     145000\n",
+       "1       33.2      54.9  Dorogobouge   Advance     140000\n",
+       "2       34.4      55.5        Chjat   Advance     127100\n",
+       "3       37.6      55.8       Moscou   Advance     100000\n",
+       "4       34.3      55.2        Wixma   Retreat      55000\n",
+       "5       32.0      54.6     Smolensk   Retreat      24000\n",
+       "6       30.4      54.4       Orscha   Retreat      20000\n",
+       "7       26.8      54.3    Moiodexno   Retreat      12000"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A common pattern is to **assign** the original name `minard` to the new table, so that all future uses of `minard` will refer to the relabeled table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>City Name</th>\n",
+       "      <th>Direction</th>\n",
+       "      <th>Survivors</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>145000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>140000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>127100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>55000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>24000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>20000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>12000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude    City Name Direction  Survivors\n",
+       "0       32.0      54.8     Smolensk   Advance     145000\n",
+       "1       33.2      54.9  Dorogobouge   Advance     140000\n",
+       "2       34.4      55.5        Chjat   Advance     127100\n",
+       "3       37.6      55.8       Moscou   Advance     100000\n",
+       "4       34.3      55.2        Wixma   Retreat      55000\n",
+       "5       32.0      54.6     Smolensk   Retreat      24000\n",
+       "6       30.4      54.4       Orscha   Retreat      20000\n",
+       "7       26.8      54.3    Moiodexno   Retreat      12000"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard = minard.rename(columns={'City':'City Name'})\n",
+    "minard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Accessing the Data in a Column\n",
+    "We can use a column's label to access the array of data in the column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    145000\n",
+       "1    140000\n",
+       "2    127100\n",
+       "3    100000\n",
+       "4     55000\n",
+       "5     24000\n",
+       "6     20000\n",
+       "7     12000\n",
+       "Name: Survivors, dtype: int64"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard['Survivors']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### type( )\n",
+    "\n",
+    "To determine the tupe of object created we can use the `type()` function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "pandas.core.frame.DataFrame"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(minard)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Using two sets of square brackets the output is displayed in DataFrame format."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Survivors</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>145000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>140000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>127100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>100000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>55000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>24000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>20000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>12000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Survivors\n",
+       "0     145000\n",
+       "1     140000\n",
+       "2     127100\n",
+       "3     100000\n",
+       "4      55000\n",
+       "5      24000\n",
+       "6      20000\n",
+       "7      12000"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard[['Survivors']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "pandas.core.frame.DataFrame"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(minard)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### iLoc[ ]\n",
+    "\n",
+    "(index location)\n",
+    "\n",
+    "The 5 columns are indexed 0, 1, 2, 3, and 4. The column `Survivors` can also be accessed by using the `iloc[]` method with the required column index. Notice that to select a column using the `iloc[]` method we have to first place a colon followed by a comma in the swuare brackets due to the default setting for `iloc[]` being set to 'rows'.\n",
+    "\n",
+    "[Pandas  iloc []](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iloc.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    145000\n",
+       "1    140000\n",
+       "2    127100\n",
+       "3    100000\n",
+       "4     55000\n",
+       "5     24000\n",
+       "6     20000\n",
+       "7     12000\n",
+       "Name: Survivors, dtype: int64"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.iloc[:,4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The 8 items in the array are indexed 0, 1, 2, and so on, up to 7. The items in the column can be accessed using `item`, as with any array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "145000"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.iloc[:,4][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "24000"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.iloc[:,4][5]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Alternatively  \n",
+    "\n",
+    "if we wish to find a particular member of a row we select a row rather than a column. Notice that in this instance we have selected the 4th row and the 4th column, remembering that though there are 5 columns Pandas refers to the first column as column 0 and first row as row 0."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "24000"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.iloc[5][4]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Working with the Data in a Column\n",
+    "Because columns are arrays, we can use array operations on them to discover new information. For example, we can create a new column that contains the percent of all survivors at each city after Smolensk."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>City Name</th>\n",
+       "      <th>Direction</th>\n",
+       "      <th>Survivors</th>\n",
+       "      <th>Percent Surviving</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>145000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>140000</td>\n",
+       "      <td>0.965517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>127100</td>\n",
+       "      <td>0.876552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>100000</td>\n",
+       "      <td>0.689655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>55000</td>\n",
+       "      <td>0.379310</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>24000</td>\n",
+       "      <td>0.165517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>20000</td>\n",
+       "      <td>0.137931</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>12000</td>\n",
+       "      <td>0.082759</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude    City Name Direction  Survivors  Percent Surviving\n",
+       "0       32.0      54.8     Smolensk   Advance     145000           1.000000\n",
+       "1       33.2      54.9  Dorogobouge   Advance     140000           0.965517\n",
+       "2       34.4      55.5        Chjat   Advance     127100           0.876552\n",
+       "3       37.6      55.8       Moscou   Advance     100000           0.689655\n",
+       "4       34.3      55.2        Wixma   Retreat      55000           0.379310\n",
+       "5       32.0      54.6     Smolensk   Retreat      24000           0.165517\n",
+       "6       30.4      54.4       Orscha   Retreat      20000           0.137931\n",
+       "7       26.8      54.3    Moiodexno   Retreat      12000           0.082759"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "initial = minard['Survivors'][0]\n",
+    "\n",
+    "minard['Percent Surviving'] = minard['Survivors']/initial\n",
+    "\n",
+    "minard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Formatting\n",
+    "\n",
+    "To make the proportions in the new columns appear as percents, we can use the method `style.format()` with the option. \n",
+    "\n",
+    "[style.format()](https://pandas.pydata.org/pandas-docs/stable/user_guide/style.html)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style  type=\"text/css\" >\n",
+       "</style><table id=\"T_091859f2_5280_11eb_bfc2_acde48001122\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >Longitude</th>        <th class=\"col_heading level0 col1\" >Latitude</th>        <th class=\"col_heading level0 col2\" >City Name</th>        <th class=\"col_heading level0 col3\" >Direction</th>        <th class=\"col_heading level0 col4\" >Survivors</th>        <th class=\"col_heading level0 col5\" >Percent Surviving</th>    </tr></thead><tbody>\n",
+       "                <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row0_col0\" class=\"data row0 col0\" >32.000000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row0_col1\" class=\"data row0 col1\" >54.800000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row0_col2\" class=\"data row0 col2\" >Smolensk</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row0_col3\" class=\"data row0 col3\" >Advance</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row0_col4\" class=\"data row0 col4\" >145000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row0_col5\" class=\"data row0 col5\" >100.00%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row1_col0\" class=\"data row1 col0\" >33.200000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row1_col1\" class=\"data row1 col1\" >54.900000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row1_col2\" class=\"data row1 col2\" >Dorogobouge</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row1_col3\" class=\"data row1 col3\" >Advance</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row1_col4\" class=\"data row1 col4\" >140000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row1_col5\" class=\"data row1 col5\" >96.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row2_col0\" class=\"data row2 col0\" >34.400000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row2_col1\" class=\"data row2 col1\" >55.500000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row2_col2\" class=\"data row2 col2\" >Chjat</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row2_col3\" class=\"data row2 col3\" >Advance</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row2_col4\" class=\"data row2 col4\" >127100</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row2_col5\" class=\"data row2 col5\" >87.66%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row3_col0\" class=\"data row3 col0\" >37.600000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row3_col1\" class=\"data row3 col1\" >55.800000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row3_col2\" class=\"data row3 col2\" >Moscou</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row3_col3\" class=\"data row3 col3\" >Advance</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row3_col4\" class=\"data row3 col4\" >100000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row3_col5\" class=\"data row3 col5\" >68.97%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row4_col0\" class=\"data row4 col0\" >34.300000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row4_col1\" class=\"data row4 col1\" >55.200000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row4_col2\" class=\"data row4 col2\" >Wixma</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row4_col3\" class=\"data row4 col3\" >Retreat</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row4_col4\" class=\"data row4 col4\" >55000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row4_col5\" class=\"data row4 col5\" >37.93%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row5_col0\" class=\"data row5 col0\" >32.000000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row5_col1\" class=\"data row5 col1\" >54.600000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row5_col2\" class=\"data row5 col2\" >Smolensk</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row5_col3\" class=\"data row5 col3\" >Retreat</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row5_col4\" class=\"data row5 col4\" >24000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row5_col5\" class=\"data row5 col5\" >16.55%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row6_col0\" class=\"data row6 col0\" >30.400000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row6_col1\" class=\"data row6 col1\" >54.400000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row6_col2\" class=\"data row6 col2\" >Orscha</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row6_col3\" class=\"data row6 col3\" >Retreat</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row6_col4\" class=\"data row6 col4\" >20000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row6_col5\" class=\"data row6 col5\" >13.79%</td>\n",
+       "            </tr>\n",
+       "            <tr>\n",
+       "                        <th id=\"T_091859f2_5280_11eb_bfc2_acde48001122level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row7_col0\" class=\"data row7 col0\" >26.800000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row7_col1\" class=\"data row7 col1\" >54.300000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row7_col2\" class=\"data row7 col2\" >Moiodexno</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row7_col3\" class=\"data row7 col3\" >Retreat</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row7_col4\" class=\"data row7 col4\" >12000</td>\n",
+       "                        <td id=\"T_091859f2_5280_11eb_bfc2_acde48001122row7_col5\" class=\"data row7 col5\" >8.28%</td>\n",
+       "            </tr>\n",
+       "    </tbody></table>"
+      ],
+      "text/plain": [
+       "<pandas.io.formats.style.Styler at 0x7fa26e3a1520>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.style.format({'Percent Surviving': \"{:.2%}\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**N.B.** a peculiarity of the Jupyter notebook is that if you make a mistake e.g. misspelling a column name, when you run the formatting function a nwe column will be created. to remive this colummn you must retart the kernel.  \n",
+    "\n",
+    "*Toolbar - Kernel - Restart & Clear Output*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Choosing Sets of Columns\n",
+    "To select particular columns we can use `df.['col1', 'col2']` which creates a new table that contains only the specified columns. When selecting a single column we can use one set of square brackets, when selecting multiple columns two sets of swuare brackets are required."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude\n",
+       "0       32.0      54.8\n",
+       "1       33.2      54.9\n",
+       "2       34.4      55.5\n",
+       "3       37.6      55.8\n",
+       "4       34.3      55.2\n",
+       "5       32.0      54.6\n",
+       "6       30.4      54.4\n",
+       "7       26.8      54.3"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard[['Longitude', 'Latitude']]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The same selection can be made using column indices instead of labels.\n",
+    "\n",
+    "**N.B.** the column range selected is 0:2 with the range being *bottom heavy*. Though the range bottom limit is 0 and the top limit is 2 instead of processing elements 0, 1 and 2 only elements 0 and 1 will be processed i.e. *bottom heavy* or *top light*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude\n",
+       "0       32.0      54.8\n",
+       "1       33.2      54.9\n",
+       "2       34.4      55.5\n",
+       "3       37.6      55.8\n",
+       "4       34.3      55.2\n",
+       "5       32.0      54.6\n",
+       "6       30.4      54.4\n",
+       "7       26.8      54.3"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.iloc[:, 0:2]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The result of using `df.[' ']` is a new DataFrame, even when you select just one column."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0    145000\n",
+       "1    140000\n",
+       "2    127100\n",
+       "3    100000\n",
+       "4     55000\n",
+       "5     24000\n",
+       "6     20000\n",
+       "7     12000\n",
+       "Name: Survivors, dtype: int64"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard['Survivors']"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Another way to create a new table consisting of a set of columns is to `drop` the columns you don't want."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>City Name</th>\n",
+       "      <th>Survivors</th>\n",
+       "      <th>Percent Surviving</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>145000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>140000</td>\n",
+       "      <td>0.965517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>127100</td>\n",
+       "      <td>0.876552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>100000</td>\n",
+       "      <td>0.689655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>55000</td>\n",
+       "      <td>0.379310</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>24000</td>\n",
+       "      <td>0.165517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>20000</td>\n",
+       "      <td>0.137931</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>12000</td>\n",
+       "      <td>0.082759</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     City Name  Survivors  Percent Surviving\n",
+       "0     Smolensk     145000           1.000000\n",
+       "1  Dorogobouge     140000           0.965517\n",
+       "2        Chjat     127100           0.876552\n",
+       "3       Moscou     100000           0.689655\n",
+       "4        Wixma      55000           0.379310\n",
+       "5     Smolensk      24000           0.165517\n",
+       "6       Orscha      20000           0.137931\n",
+       "7    Moiodexno      12000           0.082759"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard.drop(columns=['Longitude', 'Latitude', 'Direction'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Neither `df.[' ']` nor `drop` change the original DataFrame. Instead, they create new smaller DataFrames that share the same data. The fact that the original DataFrame is preserved is useful! You can generate multiple different tables that only consider certain columns without worrying that one analysis will affect the other."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Longitude</th>\n",
+       "      <th>Latitude</th>\n",
+       "      <th>City Name</th>\n",
+       "      <th>Direction</th>\n",
+       "      <th>Survivors</th>\n",
+       "      <th>Percent Surviving</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.8</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>145000</td>\n",
+       "      <td>1.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>33.2</td>\n",
+       "      <td>54.9</td>\n",
+       "      <td>Dorogobouge</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>140000</td>\n",
+       "      <td>0.965517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>34.4</td>\n",
+       "      <td>55.5</td>\n",
+       "      <td>Chjat</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>127100</td>\n",
+       "      <td>0.876552</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>37.6</td>\n",
+       "      <td>55.8</td>\n",
+       "      <td>Moscou</td>\n",
+       "      <td>Advance</td>\n",
+       "      <td>100000</td>\n",
+       "      <td>0.689655</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>34.3</td>\n",
+       "      <td>55.2</td>\n",
+       "      <td>Wixma</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>55000</td>\n",
+       "      <td>0.379310</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>32.0</td>\n",
+       "      <td>54.6</td>\n",
+       "      <td>Smolensk</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>24000</td>\n",
+       "      <td>0.165517</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>30.4</td>\n",
+       "      <td>54.4</td>\n",
+       "      <td>Orscha</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>20000</td>\n",
+       "      <td>0.137931</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>26.8</td>\n",
+       "      <td>54.3</td>\n",
+       "      <td>Moiodexno</td>\n",
+       "      <td>Retreat</td>\n",
+       "      <td>12000</td>\n",
+       "      <td>0.082759</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Longitude  Latitude    City Name Direction  Survivors  Percent Surviving\n",
+       "0       32.0      54.8     Smolensk   Advance     145000           1.000000\n",
+       "1       33.2      54.9  Dorogobouge   Advance     140000           0.965517\n",
+       "2       34.4      55.5        Chjat   Advance     127100           0.876552\n",
+       "3       37.6      55.8       Moscou   Advance     100000           0.689655\n",
+       "4       34.3      55.2        Wixma   Retreat      55000           0.379310\n",
+       "5       32.0      54.6     Smolensk   Retreat      24000           0.165517\n",
+       "6       30.4      54.4       Orscha   Retreat      20000           0.137931\n",
+       "7       26.8      54.3    Moiodexno   Retreat      12000           0.082759"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "minard"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "All of the methods that we have used above can be applied to any DataFrame."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

08/2/.ipynb_checkpoints/Classifying_by_One_Variable-checkpoint.ipynb

@@ -0,0 +1,1476 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Classifying by One Variable\n",
+    "\n",
+    "Data scientists often need to classify individuals into groups according to shared features, and then identify some characteristics of the groups. For example, in the example using Galton's data on heights, we saw that it was useful to classify families according to the parents' midparent heights, and then find the average height of the children in each group.\n",
+    "\n",
+    "This section is about classifying individuals into categories that are not numerical. We begin by recalling the basic use of `group`. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Counting the Number in Each Category\n",
+    "The `group` method with a single argument counts the number of rows for each category in a column. The result contains one row per unique value in the grouped column.\n",
+    "\n",
+    "Here is a small table of data on ice cream cones. The `group` method can be used to list the distinct flavors and provide the counts of each flavor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   6.55\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones = pd.DataFrame({\n",
+    "    'Flavor':np.array(['strawberry', 'chocolate', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.25])}\n",
+    ")\n",
+    "cones"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count\n",
+       "Flavor           \n",
+       "chocolate       3\n",
+       "strawberry      2"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_grouped = cones.groupby([\"Flavor\"]).agg(\n",
+    "    count=pd.NamedAgg(column=\"Flavor\", aggfunc=\"count\")\n",
+    ")\n",
+    "\n",
+    "df_grouped"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are two distinct categories, chocolate and strawberry. When we call `groupby` we must state what we want to do with the group data e.g. `count()`. Applying the `count()` method will create a column of counts whcih takes the names of the first column in the df by default, and contains the number of rows in each category. To make this easier to read we could change the count column to 'count'.\n",
+    "\n",
+    "Notice that this can all be worked out from just the `Flavor` column. Only the `Price` column name has been used, the data has not been used.\n",
+    "\n",
+    "But what if we wanted the total price of the cones of each different flavor? In this case we can apply a different method e.g. `sum()`, to `groupby`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Finding a Characteristic of Each Category\n",
+    "The optional second argument of `group` names the function that will be used to aggregate values in other columns for all of those rows. For instance, `sum` will sum up the prices in all rows that match each category. This result also contains one row per unique value in the grouped column, but it has the same number of columns as the original table.\n",
+    "\n",
+    "To find the total price of each flavor, we call `group` again, with `Flavor` as its first argument as before. But this time there is a second argument: the function name `sum`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price_sum</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>16.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>8.80</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Price_sum\n",
+       "Flavor               \n",
+       "chocolate       16.55\n",
+       "strawberry       8.80"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_grouped_by_price = cones.groupby([\"Flavor\"]).agg(\n",
+    "    Price_sum=pd.NamedAgg(column=\"Price\", aggfunc=\"sum\")\n",
+    ")\n",
+    "\n",
+    "df_grouped_by_price"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To create this new table, `groupby` has calculated the **sum** of the `Price` entries in all the rows corresponding to each distinct flavor. The prices in the three `chocolate` rows add up to 16.55 (in whatever currency). The prices in the two `strawberry` rows have a total of 8.80.\n",
+    "\n",
+    "Using pandas `groupby aggregation` we can compute a summary statistic (or statistics). The label of the newly created column is `Price sum`, which is created by taking the label of the column being summed, and appending the word `sum` in the *aggregation pipeline*. \n",
+    "\n",
+    "In this insatnce there are only two columns so when `group` finds the `sum` of all columns other than the one with the categories, there is no need to specify that it has to `sum` the prices. Using the [`Pandas NamedAgg`](https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#aggregation) function we can name the column contining the results of the aggregation.\n",
+    "\n",
+    "To see in more detail what `group` is doing, notice that you could have figured out the total prices yourself, not only by mental arithmetic but also using code. For example, to find the total price of all the chocolate cones, you could start by creating a new table consisting of only the chocolate cones, and then accessing the column of prices:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1    4.75\n",
+       "2    6.55\n",
+       "4    5.25\n",
+       "Name: Price, dtype: float64"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor'] == 'chocolate']['Price']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Price\n",
+       "1   4.75\n",
+       "2   6.55\n",
+       "4   5.25"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor'] == 'chocolate'][['Price']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Price    16.55\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(cones[cones['Flavor'] == 'chocolate'][['Price']])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "16.55"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum([cones[cones['Flavor'] == 'chocolate'][['Price']]])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is what `groupby` is doing for each distinct value in `Flavor`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Array of All the Prices</th>\n",
+       "      <th>Sum of the Array</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>[4.75, 6.55, 5.25]</td>\n",
+       "      <td>16.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>[3.55, 5.25]</td>\n",
+       "      <td>8.80</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor Array of All the Prices  Sum of the Array\n",
+       "0   chocolate      [4.75, 6.55, 5.25]             16.55\n",
+       "1  strawberry            [3.55, 5.25]              8.80"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# For each distinct value in `Flavor, access all the rows\n",
+    "# and create an array of `Price`\n",
+    "\n",
+    "cones_choc = cones[cones['Flavor'] == 'chocolate']['Price']\n",
+    "\n",
+    "cones_strawb = cones[cones['Flavor'] =='strawberry']['Price']\n",
+    "\n",
+    "# Display the arrays in a table\n",
+    "\n",
+    "cones_choc = np.array(cones_choc)\n",
+    "cones_strawb = np.array(cones_strawb)\n",
+    "\n",
+    "grouped_cones = pd.DataFrame({\n",
+    "    'Flavor':np.array(['chocolate', 'strawberry']),\n",
+    "    'Array of All the Prices':[cones_choc, cones_strawb]}\n",
+    ")\n",
+    "\n",
+    "#priceTotals\n",
+    "\n",
+    "# Append a column with the sum of the `Price` values in each array\n",
+    "\n",
+    "price_totals = grouped_cones\n",
+    "\n",
+    "price_totals['Sum of the Array'] = np.array([sum(cones_choc), sum(cones_strawb)])\n",
+    "\n",
+    "price_totals"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can replace `sum` by any other functions that work on arrays. For example, you could use `max` to find the largest price in each category:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Price\n",
+       "Flavor           \n",
+       "chocolate    6.55\n",
+       "strawberry   5.25"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.groupby('Flavor').max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### *Or*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price_Max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Price_Max\n",
+       "Flavor               \n",
+       "chocolate        6.55\n",
+       "strawberry       5.25"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "price_max = cones.groupby([\"Flavor\"]).agg(\n",
+    "    Price_Max=pd.NamedAgg(column=\"Price\", aggfunc=\"max\")\n",
+    ")\n",
+    "\n",
+    "price_max"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once again, `groupby` creates arrays of the prices in each `Flavor` category. But now it finds the `max` of each array:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Array of All the Prices</th>\n",
+       "      <th>Sum of the Array</th>\n",
+       "      <th>Max of the Array</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>[4.75, 6.55, 5.25]</td>\n",
+       "      <td>16.55</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>[3.55, 5.25]</td>\n",
+       "      <td>8.80</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor Array of All the Prices  Sum of the Array  Max of the Array\n",
+       "0   chocolate      [4.75, 6.55, 5.25]             16.55              6.55\n",
+       "1  strawberry            [3.55, 5.25]              8.80              5.25"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "price_max = grouped_cones.copy()\n",
+    "\n",
+    "price_max['Max of the Array'] = np.array([max(cones_choc), max(cones_strawb)])\n",
+    "\n",
+    "price_max"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Indeed, the original call to `group` with just one argument has the same effect as using `len` as the function and then cleaning up the table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Array of All the Prices</th>\n",
+       "      <th>Sum of the Array</th>\n",
+       "      <th>Length of the Array</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>[4.75, 6.55, 5.25]</td>\n",
+       "      <td>16.55</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>[3.55, 5.25]</td>\n",
+       "      <td>8.80</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor Array of All the Prices  Sum of the Array  Length of the Array\n",
+       "0   chocolate      [4.75, 6.55, 5.25]             16.55                    3\n",
+       "1  strawberry            [3.55, 5.25]              8.80                    2"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "array_length = grouped_cones.copy()\n",
+    "\n",
+    "array_length['Length of the Array'] = np.array([len(cones_choc), len(cones_strawb)])\n",
+    "\n",
+    "array_length"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example: NBA Salaries\n",
+    "The table `nba` contains data on the 2015-2016 players in the National Basketball Association. We have examined these data earlier. Recall that salaries are measured in millions of dollars."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM     SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks  18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks  12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks   9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks   8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks   5.746479\n",
+       "..               ...      ...                 ...        ...\n",
+       "412        Gary Neal       PG  Washington Wizards   2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards   2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards   1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards   1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards   0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba1 = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "\n",
+    "nba = nba1.rename(columns={\"'15-'16 SALARY\": 'SALARY'})\n",
+    "\n",
+    "nba"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**1.** How much money did each team pay for its players' salaries?\n",
+    "\n",
+    "The only columns involved are `TEAM` and `SALARY`. We have to `group` the rows by `TEAM` and then `sum` the salaries of the groups. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TEAM</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Atlanta Hawks</th>\n",
+       "      <td>69.573103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Boston Celtics</th>\n",
+       "      <td>50.285499</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Brooklyn Nets</th>\n",
+       "      <td>57.306976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Charlotte Hornets</th>\n",
+       "      <td>84.102397</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Chicago Bulls</th>\n",
+       "      <td>78.820890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Cleveland Cavaliers</th>\n",
+       "      <td>102.312412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dallas Mavericks</th>\n",
+       "      <td>65.762559</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Denver Nuggets</th>\n",
+       "      <td>62.429404</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Detroit Pistons</th>\n",
+       "      <td>42.211760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Golden State Warriors</th>\n",
+       "      <td>94.085137</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Houston Rockets</th>\n",
+       "      <td>85.285837</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Indiana Pacers</th>\n",
+       "      <td>62.695023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Los Angeles Clippers</th>\n",
+       "      <td>66.074113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Los Angeles Lakers</th>\n",
+       "      <td>68.607944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Memphis Grizzlies</th>\n",
+       "      <td>93.796439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Miami Heat</th>\n",
+       "      <td>81.528667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Milwaukee Bucks</th>\n",
+       "      <td>52.258355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Minnesota Timberwolves</th>\n",
+       "      <td>65.847421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>New Orleans Pelicans</th>\n",
+       "      <td>80.514606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>New York Knicks</th>\n",
+       "      <td>69.404994</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Oklahoma City Thunder</th>\n",
+       "      <td>96.832165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Orlando Magic</th>\n",
+       "      <td>77.623940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Philadelphia 76ers</th>\n",
+       "      <td>42.481345</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Phoenix Suns</th>\n",
+       "      <td>50.520815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Portland Trail Blazers</th>\n",
+       "      <td>45.446878</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Sacramento Kings</th>\n",
+       "      <td>68.384890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>San Antonio Spurs</th>\n",
+       "      <td>84.652074</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Toronto Raptors</th>\n",
+       "      <td>74.672620</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Utah Jazz</th>\n",
+       "      <td>52.631878</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Washington Wizards</th>\n",
+       "      <td>90.047498</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            SALARY\n",
+       "TEAM                              \n",
+       "Atlanta Hawks            69.573103\n",
+       "Boston Celtics           50.285499\n",
+       "Brooklyn Nets            57.306976\n",
+       "Charlotte Hornets        84.102397\n",
+       "Chicago Bulls            78.820890\n",
+       "Cleveland Cavaliers     102.312412\n",
+       "Dallas Mavericks         65.762559\n",
+       "Denver Nuggets           62.429404\n",
+       "Detroit Pistons          42.211760\n",
+       "Golden State Warriors    94.085137\n",
+       "Houston Rockets          85.285837\n",
+       "Indiana Pacers           62.695023\n",
+       "Los Angeles Clippers     66.074113\n",
+       "Los Angeles Lakers       68.607944\n",
+       "Memphis Grizzlies        93.796439\n",
+       "Miami Heat               81.528667\n",
+       "Milwaukee Bucks          52.258355\n",
+       "Minnesota Timberwolves   65.847421\n",
+       "New Orleans Pelicans     80.514606\n",
+       "New York Knicks          69.404994\n",
+       "Oklahoma City Thunder    96.832165\n",
+       "Orlando Magic            77.623940\n",
+       "Philadelphia 76ers       42.481345\n",
+       "Phoenix Suns             50.520815\n",
+       "Portland Trail Blazers   45.446878\n",
+       "Sacramento Kings         68.384890\n",
+       "San Antonio Spurs        84.652074\n",
+       "Toronto Raptors          74.672620\n",
+       "Utah Jazz                52.631878\n",
+       "Washington Wizards       90.047498"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "teams_and_money = nba[['TEAM', 'SALARY']]\n",
+    "\n",
+    "teams_and_money.groupby('TEAM').sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**2.** How many NBA players were there in each of the five positions?\n",
+    "\n",
+    "We have to classify by `POSITION`, and count. This can be achieved by applying the `count()` method to a `groupby` or and the aggregation method with `aggfunc=\"count\"`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>POSITION</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PF</th>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PG</th>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SF</th>\n",
+       "      <td>82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SG</th>\n",
+       "      <td>96</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          count\n",
+       "POSITION       \n",
+       "C            69\n",
+       "PF           85\n",
+       "PG           85\n",
+       "SF           82\n",
+       "SG           96"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#nba.groupby('POSITION').count()\n",
+    "\n",
+    "# -- or\n",
+    "\n",
+    "position_count = nba.groupby([\"POSITION\"]).agg(\n",
+    "    count=pd.NamedAgg(column=\"PLAYER\", aggfunc=\"count\")\n",
+    ")\n",
+    "\n",
+    "position_count"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**3.** What was the average salary of the players at each of the five positions?\n",
+    "\n",
+    "This time, we have to group by `POSITION` and take the mean of the salaries. For clarity, we will work with a table of just the positions and the salaries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>POSITION</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>6.082913</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PF</th>\n",
+       "      <td>4.951344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PG</th>\n",
+       "      <td>5.165487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SF</th>\n",
+       "      <td>5.532675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SG</th>\n",
+       "      <td>3.988195</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            SALARY\n",
+       "POSITION          \n",
+       "C         6.082913\n",
+       "PF        4.951344\n",
+       "PG        5.165487\n",
+       "SF        5.532675\n",
+       "SG        3.988195"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "positions_and_money = nba[['POSITION', 'SALARY']]\n",
+    "\n",
+    "positions_and_money.groupby('POSITION').mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Center was the most highly paid position, at an average of over 6 million dollars.\n",
+    "\n",
+    "If we had not selected the two columns as our first step, `group` would not attempt to \"average\" the categorical columns in `nba`. (It is impossible to average two strings like \"Atlanta Hawks\" and \"Boston Celtics\".) It performs arithmetic only on numerical columns and leaves the rest blank."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SALARY_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>POSITION</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>6.082913</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PF</th>\n",
+       "      <td>4.951344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PG</th>\n",
+       "      <td>5.165487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SF</th>\n",
+       "      <td>5.532675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SG</th>\n",
+       "      <td>3.988195</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          SALARY_mean\n",
+       "POSITION             \n",
+       "C            6.082913\n",
+       "PF           4.951344\n",
+       "PG           5.165487\n",
+       "SF           5.532675\n",
+       "SG           3.988195"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba_mean = nba.groupby('POSITION').mean()\n",
+    "\n",
+    "nba_mean\n",
+    "\n",
+    "nba_mean = nba.groupby([\"POSITION\"]).agg(\n",
+    "    SALARY_mean=pd.NamedAgg(column=\"SALARY\", aggfunc=\"mean\")\n",
+    ")\n",
+    "\n",
+    "nba_mean"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

08/2/Classifying_by_One_Variable.ipynb

@@ -0,0 +1,1476 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Classifying by One Variable\n",
+    "\n",
+    "Data scientists often need to classify individuals into groups according to shared features, and then identify some characteristics of the groups. For example, in the example using Galton's data on heights, we saw that it was useful to classify families according to the parents' midparent heights, and then find the average height of the children in each group.\n",
+    "\n",
+    "This section is about classifying individuals into categories that are not numerical. We begin by recalling the basic use of `group`. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Counting the Number in Each Category\n",
+    "The `group` method with a single argument counts the number of rows for each category in a column. The result contains one row per unique value in the grouped column.\n",
+    "\n",
+    "Here is a small table of data on ice cream cones. The `group` method can be used to list the distinct flavors and provide the counts of each flavor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1   chocolate   4.75\n",
+       "2   chocolate   6.55\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.25"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones = pd.DataFrame({\n",
+    "    'Flavor':np.array(['strawberry', 'chocolate', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.25])}\n",
+    ")\n",
+    "cones"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count\n",
+       "Flavor           \n",
+       "chocolate       3\n",
+       "strawberry      2"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_grouped = cones.groupby([\"Flavor\"]).agg(\n",
+    "    count=pd.NamedAgg(column=\"Flavor\", aggfunc=\"count\")\n",
+    ")\n",
+    "\n",
+    "df_grouped"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There are two distinct categories, chocolate and strawberry. When we call `groupby` we must state what we want to do with the group data e.g. `count()`. Applying the `count()` method will create a column of counts whcih takes the names of the first column in the df by default, and contains the number of rows in each category. To make this easier to read we could change the count column to 'count'.\n",
+    "\n",
+    "Notice that this can all be worked out from just the `Flavor` column. Only the `Price` column name has been used, the data has not been used.\n",
+    "\n",
+    "But what if we wanted the total price of the cones of each different flavor? In this case we can apply a different method e.g. `sum()`, to `groupby`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Finding a Characteristic of Each Category\n",
+    "The optional second argument of `group` names the function that will be used to aggregate values in other columns for all of those rows. For instance, `sum` will sum up the prices in all rows that match each category. This result also contains one row per unique value in the grouped column, but it has the same number of columns as the original table.\n",
+    "\n",
+    "To find the total price of each flavor, we call `group` again, with `Flavor` as its first argument as before. But this time there is a second argument: the function name `sum`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price_sum</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>16.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>8.80</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Price_sum\n",
+       "Flavor               \n",
+       "chocolate       16.55\n",
+       "strawberry       8.80"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_grouped_by_price = cones.groupby([\"Flavor\"]).agg(\n",
+    "    Price_sum=pd.NamedAgg(column=\"Price\", aggfunc=\"sum\")\n",
+    ")\n",
+    "\n",
+    "df_grouped_by_price"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To create this new table, `groupby` has calculated the **sum** of the `Price` entries in all the rows corresponding to each distinct flavor. The prices in the three `chocolate` rows add up to 16.55 (in whatever currency). The prices in the two `strawberry` rows have a total of 8.80.\n",
+    "\n",
+    "Using pandas `groupby aggregation` we can compute a summary statistic (or statistics). The label of the newly created column is `Price sum`, which is created by taking the label of the column being summed, and appending the word `sum` in the *aggregation pipeline*. \n",
+    "\n",
+    "In this insatnce there are only two columns so when `group` finds the `sum` of all columns other than the one with the categories, there is no need to specify that it has to `sum` the prices. Using the [`Pandas NamedAgg`](https://pandas.pydata.org/pandas-docs/stable/user_guide/groupby.html#aggregation) function we can name the column contining the results of the aggregation.\n",
+    "\n",
+    "To see in more detail what `group` is doing, notice that you could have figured out the total prices yourself, not only by mental arithmetic but also using code. For example, to find the total price of all the chocolate cones, you could start by creating a new table consisting of only the chocolate cones, and then accessing the column of prices:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1    4.75\n",
+       "2    6.55\n",
+       "4    5.25\n",
+       "Name: Price, dtype: float64"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor'] == 'chocolate']['Price']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Price\n",
+       "1   4.75\n",
+       "2   6.55\n",
+       "4   5.25"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones[cones['Flavor'] == 'chocolate'][['Price']]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Price    16.55\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum(cones[cones['Flavor'] == 'chocolate'][['Price']])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "16.55"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.sum([cones[cones['Flavor'] == 'chocolate'][['Price']]])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is what `groupby` is doing for each distinct value in `Flavor`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Array of All the Prices</th>\n",
+       "      <th>Sum of the Array</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>[4.75, 6.55, 5.25]</td>\n",
+       "      <td>16.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>[3.55, 5.25]</td>\n",
+       "      <td>8.80</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor Array of All the Prices  Sum of the Array\n",
+       "0   chocolate      [4.75, 6.55, 5.25]             16.55\n",
+       "1  strawberry            [3.55, 5.25]              8.80"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# For each distinct value in `Flavor, access all the rows\n",
+    "# and create an array of `Price`\n",
+    "\n",
+    "cones_choc = cones[cones['Flavor'] == 'chocolate']['Price']\n",
+    "\n",
+    "cones_strawb = cones[cones['Flavor'] =='strawberry']['Price']\n",
+    "\n",
+    "# Display the arrays in a table\n",
+    "\n",
+    "cones_choc = np.array(cones_choc)\n",
+    "cones_strawb = np.array(cones_strawb)\n",
+    "\n",
+    "grouped_cones = pd.DataFrame({\n",
+    "    'Flavor':np.array(['chocolate', 'strawberry']),\n",
+    "    'Array of All the Prices':[cones_choc, cones_strawb]}\n",
+    ")\n",
+    "\n",
+    "#priceTotals\n",
+    "\n",
+    "# Append a column with the sum of the `Price` values in each array\n",
+    "\n",
+    "price_totals = grouped_cones\n",
+    "\n",
+    "price_totals['Sum of the Array'] = np.array([sum(cones_choc), sum(cones_strawb)])\n",
+    "\n",
+    "price_totals"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "You can replace `sum` by any other functions that work on arrays. For example, you could use `max` to find the largest price in each category:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Price\n",
+       "Flavor           \n",
+       "chocolate    6.55\n",
+       "strawberry   5.25"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones.groupby('Flavor').max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### *Or*"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Price_Max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>strawberry</th>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            Price_Max\n",
+       "Flavor               \n",
+       "chocolate        6.55\n",
+       "strawberry       5.25"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "price_max = cones.groupby([\"Flavor\"]).agg(\n",
+    "    Price_Max=pd.NamedAgg(column=\"Price\", aggfunc=\"max\")\n",
+    ")\n",
+    "\n",
+    "price_max"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Once again, `groupby` creates arrays of the prices in each `Flavor` category. But now it finds the `max` of each array:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Array of All the Prices</th>\n",
+       "      <th>Sum of the Array</th>\n",
+       "      <th>Max of the Array</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>[4.75, 6.55, 5.25]</td>\n",
+       "      <td>16.55</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>[3.55, 5.25]</td>\n",
+       "      <td>8.80</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor Array of All the Prices  Sum of the Array  Max of the Array\n",
+       "0   chocolate      [4.75, 6.55, 5.25]             16.55              6.55\n",
+       "1  strawberry            [3.55, 5.25]              8.80              5.25"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "price_max = grouped_cones.copy()\n",
+    "\n",
+    "price_max['Max of the Array'] = np.array([max(cones_choc), max(cones_strawb)])\n",
+    "\n",
+    "price_max"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Indeed, the original call to `group` with just one argument has the same effect as using `len` as the function and then cleaning up the table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Array of All the Prices</th>\n",
+       "      <th>Sum of the Array</th>\n",
+       "      <th>Length of the Array</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>[4.75, 6.55, 5.25]</td>\n",
+       "      <td>16.55</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>[3.55, 5.25]</td>\n",
+       "      <td>8.80</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor Array of All the Prices  Sum of the Array  Length of the Array\n",
+       "0   chocolate      [4.75, 6.55, 5.25]             16.55                    3\n",
+       "1  strawberry            [3.55, 5.25]              8.80                    2"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "array_length = grouped_cones.copy()\n",
+    "\n",
+    "array_length['Length of the Array'] = np.array([len(cones_choc), len(cones_strawb)])\n",
+    "\n",
+    "array_length"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example: NBA Salaries\n",
+    "The table `nba` contains data on the 2015-2016 players in the National Basketball Association. We have examined these data earlier. Recall that salaries are measured in millions of dollars."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>PLAYER</th>\n",
+       "      <th>POSITION</th>\n",
+       "      <th>TEAM</th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Paul Millsap</td>\n",
+       "      <td>PF</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>18.671659</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Al Horford</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>12.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tiago Splitter</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>9.756250</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Jeff Teague</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>8.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Kyle Korver</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Atlanta Hawks</td>\n",
+       "      <td>5.746479</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>Gary Neal</td>\n",
+       "      <td>PG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>413</th>\n",
+       "      <td>DeJuan Blair</td>\n",
+       "      <td>C</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>2.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>414</th>\n",
+       "      <td>Kelly Oubre Jr.</td>\n",
+       "      <td>SF</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.920240</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>415</th>\n",
+       "      <td>Garrett Temple</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>1.100602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>416</th>\n",
+       "      <td>Jarell Eddie</td>\n",
+       "      <td>SG</td>\n",
+       "      <td>Washington Wizards</td>\n",
+       "      <td>0.561716</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>417 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              PLAYER POSITION                TEAM     SALARY\n",
+       "0       Paul Millsap       PF       Atlanta Hawks  18.671659\n",
+       "1         Al Horford        C       Atlanta Hawks  12.000000\n",
+       "2     Tiago Splitter        C       Atlanta Hawks   9.756250\n",
+       "3        Jeff Teague       PG       Atlanta Hawks   8.000000\n",
+       "4        Kyle Korver       SG       Atlanta Hawks   5.746479\n",
+       "..               ...      ...                 ...        ...\n",
+       "412        Gary Neal       PG  Washington Wizards   2.139000\n",
+       "413     DeJuan Blair        C  Washington Wizards   2.000000\n",
+       "414  Kelly Oubre Jr.       SF  Washington Wizards   1.920240\n",
+       "415   Garrett Temple       SG  Washington Wizards   1.100602\n",
+       "416     Jarell Eddie       SG  Washington Wizards   0.561716\n",
+       "\n",
+       "[417 rows x 4 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba1 = pd.read_csv(path_data + 'nba_salaries.csv')\n",
+    "\n",
+    "nba = nba1.rename(columns={\"'15-'16 SALARY\": 'SALARY'})\n",
+    "\n",
+    "nba"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**1.** How much money did each team pay for its players' salaries?\n",
+    "\n",
+    "The only columns involved are `TEAM` and `SALARY`. We have to `group` the rows by `TEAM` and then `sum` the salaries of the groups. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>TEAM</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>Atlanta Hawks</th>\n",
+       "      <td>69.573103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Boston Celtics</th>\n",
+       "      <td>50.285499</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Brooklyn Nets</th>\n",
+       "      <td>57.306976</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Charlotte Hornets</th>\n",
+       "      <td>84.102397</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Chicago Bulls</th>\n",
+       "      <td>78.820890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Cleveland Cavaliers</th>\n",
+       "      <td>102.312412</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Dallas Mavericks</th>\n",
+       "      <td>65.762559</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Denver Nuggets</th>\n",
+       "      <td>62.429404</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Detroit Pistons</th>\n",
+       "      <td>42.211760</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Golden State Warriors</th>\n",
+       "      <td>94.085137</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Houston Rockets</th>\n",
+       "      <td>85.285837</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Indiana Pacers</th>\n",
+       "      <td>62.695023</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Los Angeles Clippers</th>\n",
+       "      <td>66.074113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Los Angeles Lakers</th>\n",
+       "      <td>68.607944</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Memphis Grizzlies</th>\n",
+       "      <td>93.796439</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Miami Heat</th>\n",
+       "      <td>81.528667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Milwaukee Bucks</th>\n",
+       "      <td>52.258355</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Minnesota Timberwolves</th>\n",
+       "      <td>65.847421</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>New Orleans Pelicans</th>\n",
+       "      <td>80.514606</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>New York Knicks</th>\n",
+       "      <td>69.404994</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Oklahoma City Thunder</th>\n",
+       "      <td>96.832165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Orlando Magic</th>\n",
+       "      <td>77.623940</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Philadelphia 76ers</th>\n",
+       "      <td>42.481345</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Phoenix Suns</th>\n",
+       "      <td>50.520815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Portland Trail Blazers</th>\n",
+       "      <td>45.446878</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Sacramento Kings</th>\n",
+       "      <td>68.384890</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>San Antonio Spurs</th>\n",
+       "      <td>84.652074</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Toronto Raptors</th>\n",
+       "      <td>74.672620</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Utah Jazz</th>\n",
+       "      <td>52.631878</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Washington Wizards</th>\n",
+       "      <td>90.047498</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                            SALARY\n",
+       "TEAM                              \n",
+       "Atlanta Hawks            69.573103\n",
+       "Boston Celtics           50.285499\n",
+       "Brooklyn Nets            57.306976\n",
+       "Charlotte Hornets        84.102397\n",
+       "Chicago Bulls            78.820890\n",
+       "Cleveland Cavaliers     102.312412\n",
+       "Dallas Mavericks         65.762559\n",
+       "Denver Nuggets           62.429404\n",
+       "Detroit Pistons          42.211760\n",
+       "Golden State Warriors    94.085137\n",
+       "Houston Rockets          85.285837\n",
+       "Indiana Pacers           62.695023\n",
+       "Los Angeles Clippers     66.074113\n",
+       "Los Angeles Lakers       68.607944\n",
+       "Memphis Grizzlies        93.796439\n",
+       "Miami Heat               81.528667\n",
+       "Milwaukee Bucks          52.258355\n",
+       "Minnesota Timberwolves   65.847421\n",
+       "New Orleans Pelicans     80.514606\n",
+       "New York Knicks          69.404994\n",
+       "Oklahoma City Thunder    96.832165\n",
+       "Orlando Magic            77.623940\n",
+       "Philadelphia 76ers       42.481345\n",
+       "Phoenix Suns             50.520815\n",
+       "Portland Trail Blazers   45.446878\n",
+       "Sacramento Kings         68.384890\n",
+       "San Antonio Spurs        84.652074\n",
+       "Toronto Raptors          74.672620\n",
+       "Utah Jazz                52.631878\n",
+       "Washington Wizards       90.047498"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "teams_and_money = nba[['TEAM', 'SALARY']]\n",
+    "\n",
+    "teams_and_money.groupby('TEAM').sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**2.** How many NBA players were there in each of the five positions?\n",
+    "\n",
+    "We have to classify by `POSITION`, and count. This can be achieved by applying the `count()` method to a `groupby` or and the aggregation method with `aggfunc=\"count\"`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>POSITION</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PF</th>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PG</th>\n",
+       "      <td>85</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SF</th>\n",
+       "      <td>82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SG</th>\n",
+       "      <td>96</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          count\n",
+       "POSITION       \n",
+       "C            69\n",
+       "PF           85\n",
+       "PG           85\n",
+       "SF           82\n",
+       "SG           96"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#nba.groupby('POSITION').count()\n",
+    "\n",
+    "# -- or\n",
+    "\n",
+    "position_count = nba.groupby([\"POSITION\"]).agg(\n",
+    "    count=pd.NamedAgg(column=\"PLAYER\", aggfunc=\"count\")\n",
+    ")\n",
+    "\n",
+    "position_count"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**3.** What was the average salary of the players at each of the five positions?\n",
+    "\n",
+    "This time, we have to group by `POSITION` and take the mean of the salaries. For clarity, we will work with a table of just the positions and the salaries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SALARY</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>POSITION</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>6.082913</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PF</th>\n",
+       "      <td>4.951344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PG</th>\n",
+       "      <td>5.165487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SF</th>\n",
+       "      <td>5.532675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SG</th>\n",
+       "      <td>3.988195</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            SALARY\n",
+       "POSITION          \n",
+       "C         6.082913\n",
+       "PF        4.951344\n",
+       "PG        5.165487\n",
+       "SF        5.532675\n",
+       "SG        3.988195"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "positions_and_money = nba[['POSITION', 'SALARY']]\n",
+    "\n",
+    "positions_and_money.groupby('POSITION').mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Center was the most highly paid position, at an average of over 6 million dollars.\n",
+    "\n",
+    "If we had not selected the two columns as our first step, `group` would not attempt to \"average\" the categorical columns in `nba`. (It is impossible to average two strings like \"Atlanta Hawks\" and \"Boston Celtics\".) It performs arithmetic only on numerical columns and leaves the rest blank."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SALARY_mean</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>POSITION</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>6.082913</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PF</th>\n",
+       "      <td>4.951344</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PG</th>\n",
+       "      <td>5.165487</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SF</th>\n",
+       "      <td>5.532675</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>SG</th>\n",
+       "      <td>3.988195</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          SALARY_mean\n",
+       "POSITION             \n",
+       "C            6.082913\n",
+       "PF           4.951344\n",
+       "PG           5.165487\n",
+       "SF           5.532675\n",
+       "SG           3.988195"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "nba_mean = nba.groupby('POSITION').mean()\n",
+    "\n",
+    "nba_mean\n",
+    "\n",
+    "nba_mean = nba.groupby([\"POSITION\"]).agg(\n",
+    "    SALARY_mean=pd.NamedAgg(column=\"SALARY\", aggfunc=\"mean\")\n",
+    ")\n",
+    "\n",
+    "nba_mean"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

08/4/.ipynb_checkpoints/Joining_Tables_by_Columns-checkpoint.ipynb

@@ -0,0 +1,890 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Joining Tables by Columns\n",
+    "Often, data about the same individuals is maintained in more than one table. For example, one university office might have data about each student's time to completion of degree, while another has data about the student's tuition and financial aid.\n",
+    "\n",
+    "To understand the *students'* experience, it may be helpful to put the two datasets together. If the data are in two tables, each with one row per student, then we would want to put the columns together, making sure to match the rows so that each student's information remains on a single row.\n",
+    "\n",
+    "Let us do this in the context of a simple example, and then use the method with a larger dataset.\n",
+    "\n",
+    "[Pandas Merge, Join, Concatenate](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The table `cones` is one we have encountered earlier. Now suppose each flavor of ice cream comes with a rating that is in a separate table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1     vanilla   4.75\n",
+       "2   chocolate   6.55\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.75"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.75])}\n",
+    ")\n",
+    "cones"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Kind</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Kind  Stars\n",
+       "0  strawberry    2.5\n",
+       "1   chocolate    3.5\n",
+       "2     vanilla    4.0"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ratings = pd.DataFrame(\n",
+    "    {'Kind':np.array(['strawberry', 'chocolate', 'vanilla']),\n",
+    "    'Stars':np.array([2.5, 3.5, 4])}\n",
+    ")\n",
+    "ratings"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each of the tables has a column that contains ice cream flavors: `cones` has the column `Flavor`, and `ratings` has the column `Kind`. The entries in these columns can be used to link the two tables.\n",
+    "\n",
+    "The method `join` creates a new table in which each cone in the `cones` table is augmented with the Stars information in the `ratings` table.  For each cone in `cones`, `join` finds a row in `ratings` whose `Kind` matches the cone's `Flavor`.  \n",
+    "\n",
+    "In this instance we are going to `join` two df's by [`joining key columns on an index`](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-key-columns-on-an-index). To implement a `join` on an index we must create the index we wish to use in the second df, then we have to tell `join` to use those columns for matching.\n",
+    "\n",
+    "[Pandas - key columns](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-key-columns-on-an-index)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Kind</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price        Kind  Stars\n",
+       "0  strawberry   3.55  strawberry    2.5\n",
+       "1     vanilla   4.75     vanilla    4.0\n",
+       "2   chocolate   6.55   chocolate    3.5\n",
+       "3  strawberry   5.25  strawberry    2.5\n",
+       "4   chocolate   5.75   chocolate    3.5"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.75])}\n",
+    ")\n",
+    "\n",
+    "ratings = pd.DataFrame(\n",
+    "    {'Kind':np.array(['strawberry', 'chocolate', 'vanilla']),\n",
+    "     'Stars':np.array([2.5, 3.5, 4])},\n",
+    "                      index=np.array(['strawberry', 'chocolate', 'vanilla']))\n",
+    "\n",
+    "rates = cones.join(ratings, on='Flavor')\n",
+    "\n",
+    "rates"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This will create a df which includes the 'Kind' column i.e. we are repeating the flavours. To display only the columns in which we are interested -"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price  Stars\n",
+       "0  strawberry   3.55    2.5\n",
+       "1     vanilla   4.75    4.0\n",
+       "2   chocolate   6.55    3.5\n",
+       "3  strawberry   5.25    2.5\n",
+       "4   chocolate   5.75    3.5"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#rated = rates[['Flavor', 'Price', 'Stars']].sort_values(by=(['Flavor']))\n",
+    "\n",
+    "#or\n",
+    "\n",
+    "rated = rates.drop(columns=['Kind'])\n",
+    "\n",
+    "rated"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each cone now has not only its price but also the rating of its flavor.\n",
+    "\n",
+    "In general, a call to `join` that augments a table (say `table1`) with information from another table (say `table2`) looks like this:\n",
+    "\n",
+    "    table1.join(table2, table1_column_for_joining)\n",
+    "\n",
+    "The new table `rated` allows us to work out the price per star, which you can think of as an informal measure of value. Low values are good – they mean that you are paying less for each rating star."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Stars</th>\n",
+       "      <th>$/Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.187500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>1.420000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.642857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.871429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>2.100000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price  Stars   $/Price\n",
+       "1     vanilla   4.75    4.0  1.187500\n",
+       "0  strawberry   3.55    2.5  1.420000\n",
+       "4   chocolate   5.75    3.5  1.642857\n",
+       "2   chocolate   6.55    3.5  1.871429\n",
+       "3  strawberry   5.25    2.5  2.100000"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rated['$/Price'] = rated['Price'] / rated['Stars']\n",
+    "\n",
+    "rated.sort_values('$/Price')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Though strawberry has the lowest rating among the three flavors, the less expensive strawberry cone does well on this measure because it doesn't cost a lot per star."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Side note.** Does the order we list the two tables matter? Let's try it.  As you see it, this changes the order that the columns appear in, and can potentially changes the order of the rows, but it doesn't make any fundamental difference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Kind</th>\n",
+       "      <th>Stars</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>5.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Kind  Stars  Price\n",
+       "0  strawberry    2.5   3.55\n",
+       "0  strawberry    2.5   5.25\n",
+       "1   chocolate    3.5   6.55\n",
+       "1   chocolate    3.5   5.75\n",
+       "2     vanilla    4.0   4.75"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones1 = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.75])},\n",
+    "    index=np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate'])\n",
+    ")\n",
+    "\n",
+    "ratings = pd.DataFrame(\n",
+    "    {'Kind':np.array(['strawberry', 'chocolate', 'vanilla']),\n",
+    "     'Stars':np.array([2.5, 3.5, 4])})\n",
+    "\n",
+    "rates = ratings.join(cones1, on='Kind')\n",
+    "\n",
+    "rates = rates.drop(columns=['Flavor'])\n",
+    "\n",
+    "rates"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Also note that the join will only contain information about items that appear in both tables. Let's see an example. Suppose there is a table of reviews of some ice cream cones, and we have found the average or `mean` of reviews for each flavor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Flavor  Stars\n",
+       "0    vanilla      5\n",
+       "1  chocolate      3\n",
+       "2    vanilla      5\n",
+       "3  chocolate      4"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "reviews = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['vanilla', 'chocolate', 'vanilla', 'chocolate']),\n",
+    "    'Stars':np.array([5, 3, 5, 4])}\n",
+    ")\n",
+    "reviews"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Stars average</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vanilla</th>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Stars average\n",
+       "Flavor                  \n",
+       "chocolate            3.5\n",
+       "vanilla              5.0"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "average_review = reviews.groupby('Flavor').mean()\n",
+    "\n",
+    "average_review = average_review.rename(columns={'Stars':'Stars average'})\n",
+    "\n",
+    "average_review"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can join `cones` and `average_review` by providing the labels of the columns by which to join."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Stars average</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Flavor  Price  Stars average\n",
+       "2  chocolate   6.55            3.5\n",
+       "4  chocolate   5.75            3.5\n",
+       "1    vanilla   4.75            5.0"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "reviewers = cones.join(average_review, on='Flavor')\n",
+    "\n",
+    "reviewers = reviewers.rename(columns={'Stars':'Stars average'})\n",
+    "\n",
+    "reviewers = reviewers.dropna()\n",
+    "\n",
+    "reviewers.sort_values(['Stars average'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Notice how the strawberry cones have disappeared. None of the reviews are for strawberry cones, so there is nothing to which the `strawberry` rows can be joined. This might be a problem, or it might not be - that depends on the analysis we are trying to perform with the joined table."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

08/4/Joining_Tables_by_Columns.ipynb

@@ -0,0 +1,890 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Joining Tables by Columns\n",
+    "Often, data about the same individuals is maintained in more than one table. For example, one university office might have data about each student's time to completion of degree, while another has data about the student's tuition and financial aid.\n",
+    "\n",
+    "To understand the *students'* experience, it may be helpful to put the two datasets together. If the data are in two tables, each with one row per student, then we would want to put the columns together, making sure to match the rows so that each student's information remains on a single row.\n",
+    "\n",
+    "Let us do this in the context of a simple example, and then use the method with a larger dataset.\n",
+    "\n",
+    "[Pandas Merge, Join, Concatenate](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The table `cones` is one we have encountered earlier. Now suppose each flavor of ice cream comes with a rating that is in a separate table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price\n",
+       "0  strawberry   3.55\n",
+       "1     vanilla   4.75\n",
+       "2   chocolate   6.55\n",
+       "3  strawberry   5.25\n",
+       "4   chocolate   5.75"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.75])}\n",
+    ")\n",
+    "cones"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Kind</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Kind  Stars\n",
+       "0  strawberry    2.5\n",
+       "1   chocolate    3.5\n",
+       "2     vanilla    4.0"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ratings = pd.DataFrame(\n",
+    "    {'Kind':np.array(['strawberry', 'chocolate', 'vanilla']),\n",
+    "    'Stars':np.array([2.5, 3.5, 4])}\n",
+    ")\n",
+    "ratings"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each of the tables has a column that contains ice cream flavors: `cones` has the column `Flavor`, and `ratings` has the column `Kind`. The entries in these columns can be used to link the two tables.\n",
+    "\n",
+    "The method `join` creates a new table in which each cone in the `cones` table is augmented with the Stars information in the `ratings` table.  For each cone in `cones`, `join` finds a row in `ratings` whose `Kind` matches the cone's `Flavor`.  \n",
+    "\n",
+    "In this instance we are going to `join` two df's by [`joining key columns on an index`](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-key-columns-on-an-index). To implement a `join` on an index we must create the index we wish to use in the second df, then we have to tell `join` to use those columns for matching.\n",
+    "\n",
+    "[Pandas - key columns](https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html#joining-key-columns-on-an-index)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Kind</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price        Kind  Stars\n",
+       "0  strawberry   3.55  strawberry    2.5\n",
+       "1     vanilla   4.75     vanilla    4.0\n",
+       "2   chocolate   6.55   chocolate    3.5\n",
+       "3  strawberry   5.25  strawberry    2.5\n",
+       "4   chocolate   5.75   chocolate    3.5"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.75])}\n",
+    ")\n",
+    "\n",
+    "ratings = pd.DataFrame(\n",
+    "    {'Kind':np.array(['strawberry', 'chocolate', 'vanilla']),\n",
+    "     'Stars':np.array([2.5, 3.5, 4])},\n",
+    "                      index=np.array(['strawberry', 'chocolate', 'vanilla']))\n",
+    "\n",
+    "rates = cones.join(ratings, on='Flavor')\n",
+    "\n",
+    "rates"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This will create a df which includes the 'Kind' column i.e. we are repeating the flavours. To display only the columns in which we are interested -"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "      <td>2.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price  Stars\n",
+       "0  strawberry   3.55    2.5\n",
+       "1     vanilla   4.75    4.0\n",
+       "2   chocolate   6.55    3.5\n",
+       "3  strawberry   5.25    2.5\n",
+       "4   chocolate   5.75    3.5"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#rated = rates[['Flavor', 'Price', 'Stars']].sort_values(by=(['Flavor']))\n",
+    "\n",
+    "#or\n",
+    "\n",
+    "rated = rates.drop(columns=['Kind'])\n",
+    "\n",
+    "rated"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Each cone now has not only its price but also the rating of its flavor.\n",
+    "\n",
+    "In general, a call to `join` that augments a table (say `table1`) with information from another table (say `table2`) looks like this:\n",
+    "\n",
+    "    table1.join(table2, table1_column_for_joining)\n",
+    "\n",
+    "The new table `rated` allows us to work out the price per star, which you can think of as an informal measure of value. Low values are good – they mean that you are paying less for each rating star."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Stars</th>\n",
+       "      <th>$/Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>1.187500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>1.420000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.642857</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>1.871429</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>5.25</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>2.100000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Flavor  Price  Stars   $/Price\n",
+       "1     vanilla   4.75    4.0  1.187500\n",
+       "0  strawberry   3.55    2.5  1.420000\n",
+       "4   chocolate   5.75    3.5  1.642857\n",
+       "2   chocolate   6.55    3.5  1.871429\n",
+       "3  strawberry   5.25    2.5  2.100000"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rated['$/Price'] = rated['Price'] / rated['Stars']\n",
+    "\n",
+    "rated.sort_values('$/Price')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Though strawberry has the lowest rating among the three flavors, the less expensive strawberry cone does well on this measure because it doesn't cost a lot per star."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Side note.** Does the order we list the two tables matter? Let's try it.  As you see it, this changes the order that the columns appear in, and can potentially changes the order of the rows, but it doesn't make any fundamental difference."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Kind</th>\n",
+       "      <th>Stars</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>strawberry</td>\n",
+       "      <td>2.5</td>\n",
+       "      <td>5.25</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>6.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3.5</td>\n",
+       "      <td>5.75</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>4.75</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Kind  Stars  Price\n",
+       "0  strawberry    2.5   3.55\n",
+       "0  strawberry    2.5   5.25\n",
+       "1   chocolate    3.5   6.55\n",
+       "1   chocolate    3.5   5.75\n",
+       "2     vanilla    4.0   4.75"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cones1 = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate']),\n",
+    "    'Price':np.array([3.55, 4.75, 6.55, 5.25, 5.75])},\n",
+    "    index=np.array(['strawberry', 'vanilla', 'chocolate', 'strawberry', 'chocolate'])\n",
+    ")\n",
+    "\n",
+    "ratings = pd.DataFrame(\n",
+    "    {'Kind':np.array(['strawberry', 'chocolate', 'vanilla']),\n",
+    "     'Stars':np.array([2.5, 3.5, 4])})\n",
+    "\n",
+    "rates = ratings.join(cones1, on='Kind')\n",
+    "\n",
+    "rates = rates.drop(columns=['Flavor'])\n",
+    "\n",
+    "rates"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Also note that the join will only contain information about items that appear in both tables. Let's see an example. Suppose there is a table of reviews of some ice cream cones, and we have found the average or `mean` of reviews for each flavor."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Stars</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Flavor  Stars\n",
+       "0    vanilla      5\n",
+       "1  chocolate      3\n",
+       "2    vanilla      5\n",
+       "3  chocolate      4"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "reviews = pd.DataFrame(\n",
+    "    {'Flavor':np.array(['vanilla', 'chocolate', 'vanilla', 'chocolate']),\n",
+    "    'Stars':np.array([5, 3, 5, 4])}\n",
+    ")\n",
+    "reviews"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Stars average</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Flavor</th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>chocolate</th>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>vanilla</th>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Stars average\n",
+       "Flavor                  \n",
+       "chocolate            3.5\n",
+       "vanilla              5.0"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "average_review = reviews.groupby('Flavor').mean()\n",
+    "\n",
+    "average_review = average_review.rename(columns={'Stars':'Stars average'})\n",
+    "\n",
+    "average_review"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We can join `cones` and `average_review` by providing the labels of the columns by which to join."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Flavor</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Stars average</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>chocolate</td>\n",
+       "      <td>5.75</td>\n",
+       "      <td>3.5</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>vanilla</td>\n",
+       "      <td>4.75</td>\n",
+       "      <td>5.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Flavor  Price  Stars average\n",
+       "2  chocolate   6.55            3.5\n",
+       "4  chocolate   5.75            3.5\n",
+       "1    vanilla   4.75            5.0"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "reviewers = cones.join(average_review, on='Flavor')\n",
+    "\n",
+    "reviewers = reviewers.rename(columns={'Stars':'Stars average'})\n",
+    "\n",
+    "reviewers = reviewers.dropna()\n",
+    "\n",
+    "reviewers.sort_values(['Stars average'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Notice how the strawberry cones have disappeared. None of the reviews are for strawberry cones, so there is nothing to which the `strawberry` rows can be joined. This might be a problem, or it might not be - that depends on the analysis we are trying to perform with the joined table."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

08/Functions_and_Tables.ipynb

@@ -0,0 +1,467 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "path_data = '../../image/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 8. Functions and Tables"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "(**N.B.** when using the term 'Table(s)' we are referring to DataFrames)\n",
+    "\n",
+    "We are building up a useful inventory of techniques for identifying patterns and themes in a data set by using functions already available in Python. We will now explore a core feature of the Python programming language: function definition.\n",
+    "\n",
+    "We have used functions extensively already in this text, but never defined a function of our own. The purpose of defining a function is to give a name to a computational process that may be applied multiple times. There are many situations in computing that require repeated computation. For example, it is often the case that we want to perform the same manipulation on every value in a column of a table."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Defining a Function\n",
+    "The definition of the `double` function below simply doubles a number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Our first function definition\n",
+    "\n",
+    "def double(x):\n",
+    "    \"\"\" Double x \"\"\"\n",
+    "    return 2*x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We start any function definition by writing `def`.  Here is a breakdown of the other parts (the *syntax*) of this small function:\n",
+    "\n",
+    "![](../../images/function_definition.jpg)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "When we run the cell above, no particular number is doubled, and the code inside the body of `double` is not yet evaluated.  In this respect, our function is analogous to a *recipe*.  Each time we follow the instructions in a recipe, we need to start with ingredients.  Each time we want to use our function to double a number, we need to specify a number.\n",
+    "\n",
+    "We can call `double` in exactly the same way we have called other functions. Each time we do that, the code in the body is executed, with the value of the argument given the name `x`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "34"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "double(17)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.3"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "double(-0.6/4)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The two expressions above are both *call expressions*. In the second one, the value of the expression `-0.6/4` is computed and then passed as the argument named `x` to the `double` function. Each call expresson results in the body of `double` being executed, but with a different value of `x`.\n",
+    "\n",
+    "The body of `double` has only a single line:\n",
+    "\n",
+    "`return 2*x`\n",
+    "\n",
+    "Executing this *`return` statement* completes execution of the `double` function's body and computes the value of the call expression.\n",
+    "\n",
+    "The argument to `double` can be any expression, as long as its value is a number.  For example, it can be a name.  The `double` function does not know or care how its argument is computed or stored; its only job is to execute its own body using the values of the arguments passed to it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "84"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "any_name = 42\n",
+    "double(any_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The argument can also be any value that can be doubled. For example, a whole array of numbers can be passed as an argument to `double`, and the result will be another array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([ 6,  8, 10])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "double(np.array([3, 4, 5]))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "However, names that are defined inside a function, including arguments like `double`'s `x`, have only a fleeting existence.  They are defined only while the function is being called, and they are only accessible inside the body of the function. We can't refer to `x` outside the body of `double`. The technical terminology is that `x` has *local scope*.\n",
+    "\n",
+    "Therefore the name `x` isn't recognized outside the body of the function, even though we have called `double` in the cells above."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "tags": [
+     "raises-exception"
+    ]
+   },
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'x' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-34-6fcf9dfbd479>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m: name 'x' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Docstrings.** Though `double` is relatively easy to understand, many functions perform complicated tasks and are difficult to use without explanation. (You may have discovered this yourself!) Therefore, a well-composed function has a name that evokes its behavior, as well as documentation.  In Python, this is called a *docstring* — a description of its behavior and expectations about its arguments. The docstring can also show example calls to the function, where the call is preceded by `>>>`.\n",
+    "\n",
+    "A docstring can be any string, as long as it is the first thing in a function's body. Docstrings are typically defined using triple quotation marks at the start and end, which allows a string to span multiple lines. The first line is conventionally a complete but short description of the function, while following lines provide further guidance to future users of the function.\n",
+    "\n",
+    "Here is a definition of a function called `percent` that takes two arguments. The definition includes a docstring."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# A function with more than one argument\n",
+    "\n",
+    "def percent(x, total):\n",
+    "    \"\"\"Convert x to a percentage of total.\n",
+    "    \n",
+    "    More precisely, this function divides x by total,\n",
+    "    multiplies the result by 100, and rounds the result\n",
+    "    to two decimal places.\n",
+    "    \n",
+    "    >>> percent(4, 16)\n",
+    "    25.0\n",
+    "    >>> percent(1, 6)\n",
+    "    16.67\n",
+    "    \"\"\"\n",
+    "    return round((x/total)*100, 2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "16.5"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "percent(33, 200)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Contrast the function `percent` defined above with the function `percents` defined below. The latter takes an array as its argument, and converts all the numbers in the array to percents out of the total of the values in the array. The percents are all rounded to two decimal places, this time replacing `round` by `np.round` because the argument is an array and not a number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def percents(counts):\n",
+    "    \"\"\"Convert the values in array_x to percents out of the total of array_x.\"\"\"\n",
+    "    total = counts.sum()\n",
+    "    return np.round((counts/total)*100, 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The function `percents` returns an array of percents that add up to 100 apart from rounding."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([33.33, 47.62, 19.05])"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "some_array = np.array([7, 10, 4])\n",
+    "percents(some_array)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "It is helpful to understand the steps Python takes to execute a function.  To facilitate this, we have put a function definition and a call to that function in the same cell below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The biggest difference is 5\n"
+     ]
+    }
+   ],
+   "source": [
+    "def biggest_difference(array_x):\n",
+    "    \"\"\"Find the biggest difference in absolute value between two adjacent elements of array_x.\"\"\"\n",
+    "    diffs = np.diff(array_x)\n",
+    "    absolute_diffs = abs(diffs)\n",
+    "    return max(absolute_diffs)\n",
+    "\n",
+    "some_numbers = np.array([2, 4, 5, 6, 4, -1, 1])\n",
+    "big_diff = biggest_difference(some_numbers)\n",
+    "print(\"The biggest difference is\", big_diff)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here is what happens when we run that cell:\n",
+    "\n",
+    "![Function_Execution](function_execution.jpg)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Multiple Arguments"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "There can be multiple ways to generalize an expression or block of code, and so a function can take multiple arguments that each determine different aspects of the result. For example, the `percents` function we defined previously rounded to two decimal places every time. The following two-argument definition allows different calls to round to different amounts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Rounded to 1 decimal place:  [28.6 14.3 57.1]\n",
+      "Rounded to 2 decimal places: [28.57 14.29 57.14]\n",
+      "Rounded to 3 decimal places: [28.571 14.286 57.143]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def percents(counts, decimal_places):\n",
+    "    \"\"\"Convert the values in array_x to percents out of the total of array_x.\"\"\"\n",
+    "    total = counts.sum()\n",
+    "    return np.round((counts/total)*100, decimal_places)\n",
+    "\n",
+    "parts = np.array([2, 1, 4])\n",
+    "print(\"Rounded to 1 decimal place: \", percents(parts, 1))\n",
+    "print(\"Rounded to 2 decimal places:\", percents(parts, 2))\n",
+    "print(\"Rounded to 3 decimal places:\", percents(parts, 3))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The flexibility of this new definition comes at a small price: each time the function is called, the number of decimal places must be specified. Default argument values allow a function to be called with a variable number of arguments; any argument that isn't specified in the call expression is given its default value, which is stated in the first line of the `def` statement. For example, in this final definition of `percents`, the optional argument `decimal_places` is given a default value of 2."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Rounded to 1 decimal place: [28.6 14.3 57.1]\n",
+      "Rounded to the default number of decimal places: [28.57 14.29 57.14]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def percents(counts, decimal_places=2):\n",
+    "    \"\"\"Convert the values in array_x to percents out of the total of array_x.\"\"\"\n",
+    "    total = counts.sum()\n",
+    "    return np.round((counts/total)*100, decimal_places)\n",
+    "\n",
+    "parts = np.array([2, 1, 4])\n",
+    "print(\"Rounded to 1 decimal place:\", percents(parts, 1))\n",
+    "print(\"Rounded to the default number of decimal places:\", percents(parts))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Note: Methods\n",
+    "Functions are called by placing argument expressions in parentheses after the function name. Any function that is defined in isolation is called in this way. You have also seen examples of methods, which are like functions but are called using dot notation, such as `some_table.sort_values(some_label)`. The functions that you define will always be called using the function name first, passing in all of the arguments.  \n",
+    "\n",
+    "**N.B.** remember - a table is another name for a df"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

09/1/.ipynb_checkpoints/Conditional_Statements-checkpoint.ipynb

@@ -0,0 +1,383 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Conditional Statements\n",
+    "In many situations, actions and results depends on a specific set of conditions being satisfied. For example, individuals in randomized controlled trials receive the treatment if they have been assigned to the treatment group. A gambler makes money if she wins her bet. \n",
+    "\n",
+    "In this section we will learn how to describe such situations using code. A *conditional statement* is a multi-line statement that allows Python to choose among different alternatives based on the truth value of an expression. While conditional statements can appear anywhere, they appear most often within the body of a function in order to express alternative behavior depending on argument values.\n",
+    "\n",
+    "A conditional statement always begins with an `if` header, which is a single line followed by an indented body. The body is only executed if the expression directly following `if` (called the *if expression*) evaluates to a true value. If the *if expression* evaluates to a false value, then the body of the `if` is skipped.\n",
+    "\n",
+    "Let us start defining a function that returns the sign of a number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Positive'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function returns the correct sign if the input is a positive number. But if the input is not a positive number, then the *if expression* evaluates to a false value, and so the `return` statement is skipped and the function call has no value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sign(-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So let us refine our function to return `Negative` if the input is a negative number. We can do this by adding an `elif` clause, where `elif` if Python's shorthand for the phrase \"else, if\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'\n",
+    "    \n",
+    "    elif x < 0:\n",
+    "        return 'Negative'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now `sign` returns the correct answer when the input is -3:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Negative'"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What if the input is 0? To deal with this case, we can add another `elif` clause:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'\n",
+    "    \n",
+    "    elif x < 0:\n",
+    "        return 'Negative'\n",
+    "    \n",
+    "    elif x == 0:\n",
+    "        return 'Neither positive nor negative'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Neither positive nor negative'"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Equivalently, we can replaced the final `elif` clause by an `else` clause, whose body will be executed only if all the previous comparisons are false; that is, if the input value is equal to 0."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'\n",
+    "    \n",
+    "    elif x < 0:\n",
+    "        return 'Negative'\n",
+    "    \n",
+    "    else:\n",
+    "        return 'Neither positive nor negative'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Neither positive nor negative'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## The General Form ###\n",
+    "A conditional statement can also have multiple clauses with multiple bodies, and only one of those bodies can ever be executed. The general format of a multi-clause conditional statement appears below.\n",
+    "\n",
+    "    if <if expression>:\n",
+    "        <if body>\n",
+    "    elif <elif expression 0>:\n",
+    "        <elif body 0>\n",
+    "    elif <elif expression 1>:\n",
+    "        <elif body 1>\n",
+    "    ...\n",
+    "    else:\n",
+    "        <else body>\n",
+    "        \n",
+    "There is always exactly one `if` clause, but there can be any number of `elif` clauses. Python will evaluate the `if` and `elif` expressions in the headers in order until one is found that is a true value, then execute the corresponding body. The `else` clause is optional. When an `else` header is provided, its *else body* is executed only if none of the header expressions of the previous clauses are true. The `else` clause must always come at the end (or not at all)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example: Betting on a Die\n",
+    "Suppose I bet on a roll of a fair die. The rules of the game:\n",
+    "\n",
+    "- If the die shows 1 spot or 2 spots, I lose a dollar.\n",
+    "- If the die shows 3 spots or 4 spots, I neither lose money nor gain money.\n",
+    "- If the die shows 5 spots or 6 spots, I gain a dollar.\n",
+    "\n",
+    "We will now use conditional statements to define a function `one_bet` that takes the number of spots on the roll and returns my net gain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def one_bet(x):\n",
+    "    \"\"\"Returns my net gain if the die shows x spots\"\"\"\n",
+    "    if x <= 2:\n",
+    "        return -1\n",
+    "    elif x <= 4:\n",
+    "        return 0\n",
+    "    elif x <= 6:\n",
+    "        return 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's check that the function does the right thing for each different number of spots."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-1, -1, 0, 0, 1, 1)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "one_bet(1), one_bet(2), one_bet(3), one_bet (4), one_bet(5), one_bet(6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As a review of how conditional statements work, let's see what `one_bet` does when the input is 3.\n",
+    "\n",
+    "- First it evaluates the `if` expression, which is `3 <= 2` which is `False`. So `one_bet` doesn't execute the `if` body.\n",
+    "- Then it evaluates the first `elif` expression, which is `3 <= 4`, which is `True`. So `one_bet` executes the first `elif` body and returns 0.\n",
+    "- Once the body has been executed, the process is complete. The next `elif` expression is not evaluated.\n",
+    "\n",
+    "If for some reason we use an input greater than 6, then the `if` expression evaluates to `False` as do both of the `elif` expressions. So `one_bet` does not execute the `if` body nor the two `elif` bodies, and there is no value when you make the call below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "one_bet(17)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To play the game based on one roll of a die, you can use `np.random.choice` to generate the number of spots and then use that as the argument to `one_bet`. Run the cell a few times to see how the output changes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "one_bet(np.random.choice(np.arange(1, 7)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "At this point it is natural to want to collect the results of all the bets so that we can analyze them. In the next section we develop a way to do this without running the cell over and over again."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

09/1/Conditional_Statements.ipynb

@@ -0,0 +1,383 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Conditional Statements\n",
+    "In many situations, actions and results depends on a specific set of conditions being satisfied. For example, individuals in randomized controlled trials receive the treatment if they have been assigned to the treatment group. A gambler makes money if she wins her bet. \n",
+    "\n",
+    "In this section we will learn how to describe such situations using code. A *conditional statement* is a multi-line statement that allows Python to choose among different alternatives based on the truth value of an expression. While conditional statements can appear anywhere, they appear most often within the body of a function in order to express alternative behavior depending on argument values.\n",
+    "\n",
+    "A conditional statement always begins with an `if` header, which is a single line followed by an indented body. The body is only executed if the expression directly following `if` (called the *if expression*) evaluates to a true value. If the *if expression* evaluates to a false value, then the body of the `if` is skipped.\n",
+    "\n",
+    "Let us start defining a function that returns the sign of a number."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Positive'"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This function returns the correct sign if the input is a positive number. But if the input is not a positive number, then the *if expression* evaluates to a false value, and so the `return` statement is skipped and the function call has no value."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sign(-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So let us refine our function to return `Negative` if the input is a negative number. We can do this by adding an `elif` clause, where `elif` if Python's shorthand for the phrase \"else, if\"."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'\n",
+    "    \n",
+    "    elif x < 0:\n",
+    "        return 'Negative'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now `sign` returns the correct answer when the input is -3:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Negative'"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(-3)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "What if the input is 0? To deal with this case, we can add another `elif` clause:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'\n",
+    "    \n",
+    "    elif x < 0:\n",
+    "        return 'Negative'\n",
+    "    \n",
+    "    elif x == 0:\n",
+    "        return 'Neither positive nor negative'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Neither positive nor negative'"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Equivalently, we can replaced the final `elif` clause by an `else` clause, whose body will be executed only if all the previous comparisons are false; that is, if the input value is equal to 0."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def sign(x):\n",
+    "    \n",
+    "    if x > 0:\n",
+    "        return 'Positive'\n",
+    "    \n",
+    "    elif x < 0:\n",
+    "        return 'Negative'\n",
+    "    \n",
+    "    else:\n",
+    "        return 'Neither positive nor negative'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Neither positive nor negative'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sign(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## The General Form ###\n",
+    "A conditional statement can also have multiple clauses with multiple bodies, and only one of those bodies can ever be executed. The general format of a multi-clause conditional statement appears below.\n",
+    "\n",
+    "    if <if expression>:\n",
+    "        <if body>\n",
+    "    elif <elif expression 0>:\n",
+    "        <elif body 0>\n",
+    "    elif <elif expression 1>:\n",
+    "        <elif body 1>\n",
+    "    ...\n",
+    "    else:\n",
+    "        <else body>\n",
+    "        \n",
+    "There is always exactly one `if` clause, but there can be any number of `elif` clauses. Python will evaluate the `if` and `elif` expressions in the headers in order until one is found that is a true value, then execute the corresponding body. The `else` clause is optional. When an `else` header is provided, its *else body* is executed only if none of the header expressions of the previous clauses are true. The `else` clause must always come at the end (or not at all)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Example: Betting on a Die\n",
+    "Suppose I bet on a roll of a fair die. The rules of the game:\n",
+    "\n",
+    "- If the die shows 1 spot or 2 spots, I lose a dollar.\n",
+    "- If the die shows 3 spots or 4 spots, I neither lose money nor gain money.\n",
+    "- If the die shows 5 spots or 6 spots, I gain a dollar.\n",
+    "\n",
+    "We will now use conditional statements to define a function `one_bet` that takes the number of spots on the roll and returns my net gain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def one_bet(x):\n",
+    "    \"\"\"Returns my net gain if the die shows x spots\"\"\"\n",
+    "    if x <= 2:\n",
+    "        return -1\n",
+    "    elif x <= 4:\n",
+    "        return 0\n",
+    "    elif x <= 6:\n",
+    "        return 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's check that the function does the right thing for each different number of spots."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-1, -1, 0, 0, 1, 1)"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "one_bet(1), one_bet(2), one_bet(3), one_bet (4), one_bet(5), one_bet(6)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As a review of how conditional statements work, let's see what `one_bet` does when the input is 3.\n",
+    "\n",
+    "- First it evaluates the `if` expression, which is `3 <= 2` which is `False`. So `one_bet` doesn't execute the `if` body.\n",
+    "- Then it evaluates the first `elif` expression, which is `3 <= 4`, which is `True`. So `one_bet` executes the first `elif` body and returns 0.\n",
+    "- Once the body has been executed, the process is complete. The next `elif` expression is not evaluated.\n",
+    "\n",
+    "If for some reason we use an input greater than 6, then the `if` expression evaluates to `False` as do both of the `elif` expressions. So `one_bet` does not execute the `if` body nor the two `elif` bodies, and there is no value when you make the call below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "one_bet(17)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To play the game based on one roll of a die, you can use `np.random.choice` to generate the number of spots and then use that as the argument to `one_bet`. Run the cell a few times to see how the output changes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "one_bet(np.random.choice(np.arange(1, 7)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "At this point it is natural to want to collect the results of all the bets so that we can analyze them. In the next section we develop a way to do this without running the cell over and over again."
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}

09/Randomness.ipynb

@@ -0,0 +1,394 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "tags": [
+     "remove_input"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "path_data = '../../data/'\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.style.use('fivethirtyeight')\n",
+    "\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 9. Randomness\n",
+    "\n",
+    "In the previous chapters we developed skills needed to make insightful *descriptions* of data. Data scientists also have to be able to understand **randomness**. For example, they have to be able to assign individuals to treatment and control groups at random, and then try to say whether any observed differences in the outcomes of the two groups are simply due to the random assignment or genuinely due to the treatment.\n",
+    "\n",
+    "In this chapter, we begin our analysis of randomness. To start off, we will use Python to make choices at random. In `numpy` there is a sub-module called `random` that contains many functions that involve random selection. One of these functions is called `choice`. It picks one item at random from an array, and it is equally likely to pick any of the items. The function call is `np.random.choice(array_name)`, where `array_name` is the name of the array from which to make the choice.\n",
+    "\n",
+    "Thus the following code evaluates to `treatment` with chance 50%, and `control` with chance 50%."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'control'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "two_groups = np.array(['treatment', 'control'])\n",
+    "np.random.choice(two_groups)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The big difference between the code above and all the other code we have run thus far is that the code above doesn't always return the same value. It can return either `treatment` or `control`, and we don't know ahead of time which one it will pick. We can repeat the process by providing a second argument, the number of times to repeat the process."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['treatment', 'control', 'control', 'treatment', 'treatment',\n",
+       "       'treatment', 'control', 'treatment', 'treatment', 'treatment'],\n",
+       "      dtype='<U9')"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.random.choice(two_groups, 10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "A fundamental question about random events is whether or not they occur. For example:\n",
+    "\n",
+    "- Did an individual get assigned to the treatment group, or not?\n",
+    "- Is a gambler going to win money, or not?\n",
+    "- Has a poll made an accurate prediction, or not?\n",
+    "\n",
+    "Once the event has occurred, you can answer \"yes\" or \"no\" to all these questions. In programming, it is conventional to do this by labeling statements as True or False. For example, if an individual did get assigned to the treatment group, then the statement, \"The individual was assigned to the treatment group\" would be `True`. If not, it would be `False`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Booleans and Comparison\n",
+    "\n",
+    "In Python, Boolean values, named for the logician [George Boole](https://en.wikipedia.org/wiki/George_Boole), represent truth and take only two possible values: `True` and `False`. Whether problems involve randomness or not, Boolean values most often arise from comparison operators. Python includes a variety of operators that compare values. For example, `3` is larger than `1 + 1`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "3 > 1 + 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The value `True` indicates that the comparison is valid; Python has confirmed this simple fact about the relationship between `3` and `1+1`. The full set of common comparison operators are listed below.\n",
+    "\n",
+    "| Comparison         | Operator | True example | False Example |\n",
+    "|--------------------|----------|--------------|---------------|\n",
+    "| Less than          | <        | 2 < 3        | 2 < 2         |\n",
+    "| Greater than       | >        | 3 > 2        | 3 > 3         |\n",
+    "| Less than or equal | <=       | 2 <= 2       | 3 <= 2        |\n",
+    "| Greater or equal   | >=       | 3 >= 3       | 2 >= 3        |\n",
+    "| Equal              | ==       | 3 == 3       | 3 == 2        |\n",
+    "| Not equal          | !=       | 3 != 2       | 2 != 2        |"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Notice the two equal signs `==` in the comparison to determine equality. This is necessary because Python already uses `=` to mean assignment to a name, as we have seen. It can't use the same symbol for a different purpose. Thus if you want to check whether 5 is equal to the 10/2, then you have to be careful: `5 = 10/2` returns an error message because Python assumes you are trying to assign the value of the expression 10/2 to a name that is the numeral 5. Instead, you must use `5 == 10/2`, which evaluates to `True`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "tags": [
+     "raises-exception"
+    ]
+   },
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "cannot assign to literal (<ipython-input-5-e8c755f5e450>, line 1)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-5-e8c755f5e450>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    5 = 10/2\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m cannot assign to literal\n"
+     ]
+    }
+   ],
+   "source": [
+    "5 = 10/2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "5 == 10/2"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "An expression can contain multiple comparisons, and they all must hold in order for the whole expression to be `True`. For example, we can express that `1+1` is between `1` and `3` using the following expression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "1 < 1 + 1 < 3"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The average of two numbers is always between the smaller number and the larger number. We express this relationship for the numbers `x` and `y` below. You can try different values of `x` and `y` to confirm this relationship."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x = 12\n",
+    "y = 5\n",
+    "min(x, y) <= (x+y)/2 <= max(x, y)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Comparing Strings\n",
+    "\n",
+    "Strings can also be compared, and their order is alphabetical. A shorter string is less than a longer string that begins with the shorter string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "'Dog' > 'Catastrophe' > 'Cat'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's return to random selection. Recall the array `two_groups` which consists of just two elements, `treatment` and `control`. To see whether a randomly assigned individual went to the treatment group, you can use a comparison:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.random.choice(two_groups) == 'treatment'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As before, the random choice will not always be the same, so the result of the comparison won't always be the same either. It will depend on whether `treatment` or `control` was chosen. With any cell that involves random selection, it is a good idea to run the cell several times to get a sense of the variability in the result."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Comparing an Array and a Value\n",
+    "Recall that we can perform arithmetic operations on many numbers in an array at once.  For example, `make_array(0, 5, 2)*2` is equivalent to `make_array(0, 10, 4)`.  In similar fashion, if we compare an array and one value, each element of the array is compared to that value, and the comparison evaluates to an array of Booleans."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([False,  True, False,  True,  True])"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tosses = np.array(['Tails', 'Heads', 'Tails', 'Heads', 'Heads'])\n",
+    "tosses == 'Heads'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The `numpy` method `count_nonzero` evaluates to the number of non-zero (that is, `True`) elements of the array."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "3"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.count_nonzero(tosses == 'Heads')"
+   ]
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}