{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"tags": [
"remove_input"
]
},
"outputs": [],
"source": [
"path_data = '../data/'\n",
"path_images = '../images/'\n",
"\n",
"import pandas as pd\n",
"import matplotlib\n",
"\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"plt.style.use('bmh')\n",
"\n",
"import warnings\n",
"warnings.filterwarnings('ignore')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# 7. Visualization"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Tables are a powerful way of organizing and visualizing data. However, large tables of numbers can be difficult to interpret, no matter how organized they are. Sometimes it is much easier to interpret graphs than numbers.\n",
"\n",
"In this chapter we will develop some of the fundamental graphical methods of data analysis. Our source of data is the [Internet Movie Database](http://www.imdb.com), an online database that contains information about movies, television shows, video games, and so on. The site [Box Office Mojo](http://www.boxofficemojo.com) provides many summaries of IMDB data, some of which we have adapted. We have also used data summaries from [The Numbers](http://www.the-numbers.com), a site with a tagline that says it is \"where data and the movie business meet.\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Scatter Plots and Line Graphs"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The table `actors` contains data on Hollywood actors, both male and female. The columns are:\n",
"\n",
"| ** Column ** | Contents |\n",
"|---------------------|----------|\n",
"|`Actor` | Name of actor |\n",
"|`Total Gross` | Total gross domestic box office receipt, in millions of dollars, of all of the actor's movies |\n",
"| `Number of Movies` | The number of movies the actor has been in |\n",
"| `Average per Movie` | Total gross divided by number of movies |\n",
"| `#1 Movie` | The highest grossing movie the actor has been in |\n",
"| `Gross` | Gross domestic box office receipt, in millions of dollars, of the actor's `#1 Movie` |\n",
"\n",
"In the calculation of the gross receipt, the data tabulators did not include movies where an actor had a cameo role or a speaking role that did not involve much screen time.\n",
"\n",
"The table has 50 rows, corresponding to the 50 top grossing actors. The table is already sorted by `Total Gross`, so it is easy to see that Harrison Ford is the highest grossing actor. In total, his movies have brought in more money at domestic box office than the movies of any other actor."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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Actor
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Total Gross
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0
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Star Wars: The Force Awakens
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936.7
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Samuel L. Jackson
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The Avengers
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Morgan Freeman
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The Dark Knight
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Tom Hanks
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Toy Story 3
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415.0
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Robert Downey, Jr.
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"text/plain": [
" Actor Total Gross Number of Movies Average per Movie \\\n",
"0 Harrison Ford 4871.7 41 118.8 \n",
"1 Samuel L. Jackson 4772.8 69 69.2 \n",
"2 Morgan Freeman 4468.3 61 73.3 \n",
"3 Tom Hanks 4340.8 44 98.7 \n",
"4 Robert Downey, Jr. 3947.3 53 74.5 \n",
"\n",
" #1 Movie Gross \n",
"0 Star Wars: The Force Awakens 936.7 \n",
"1 The Avengers 623.4 \n",
"2 The Dark Knight 534.9 \n",
"3 Toy Story 3 415.0 \n",
"4 The Avengers 623.4 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"actors = pd.read_csv(path_data + 'actors.csv')\n",
"actors.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Terminology.**\n",
"A *variable* is a formal name for what we have been calling a \"feature\", such as 'number of movies.' The term *variable* emphasizes that the feature can have different values for different individuals – the numbers of movies that actors have been in varies across all the actors.\n",
"\n",
"Variables that have numerical values, such as 'number of movies' or 'average gross receipts per movie' are called *quantitative* or *numerical* variables."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Scatter Plots\n",
"A *scatter plot* displays the relation between two numerical variables. You saw an example of a scatter plot in an early section where we looked at the number of periods and number of characters in two classic novels.\n",
"\n",
"The matplotlib method `scatter` draws a scatter plot consisting of one point for each row of the DataFrame. Its first argument is the label of the column to be plotted on the horizontal axis, and its second argument is the label of the column on the vertical. \n",
"\n",
"[matplotlib Usage](https://matplotlib.org/tutorials/introductory/usage.html#sphx-glr-tutorials-introductory-usage-py)\n",
"\n",
"[matplotlib style](https://matplotlib.org/3.1.1/gallery/style_sheets/style_sheets_reference.html) Restart and clear kernel to apply. To get an idea of the effect of style uncomment (remove the hash symbol) the instruction `#plots.style.use('fivethirtyeight')`\n",
"and comment `plots.style.use('bmh')` in the first cell of this notebook (import cell).\n",
"\n",
"[matplotlib legend](https://matplotlib.org/3.1.0/api/_as_gen/matplotlib.pyplot.legend.html)\n",
"\n",
"[matplotlib scatter](https://matplotlib.org/3.3.3/api/_as_gen/matplotlib.pyplot.scatter.html)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### matplotlib scatter plot"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x = actors['Number of Movies']\n",
"y = actors['Total Gross']\n",
"\n",
"fig, ax = plt.subplots()\n",
"\n",
"ax.scatter(x, y, c='red', label='Gross/#Movies', edgecolors='black')\n",
"ax.set_title('Gross Vs Number Movies')\n",
"ax.set_xlabel('Number of Movies')\n",
"ax.set_ylabel('Total Gross')\n",
"\n",
"\n",
"\n",
"legend = ax.legend(loc='upper left', shadow=True, fontsize='x-large')\n",
"\n",
"# Put a nicer background color on the legend.\n",
"legend.get_frame().set_facecolor('white')\n",
"\n",
"plt.show()\n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Pandas scatter plot"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"actors.plot.scatter(x = 'Number of Movies', y = 'Total Gross', c='red', label='Gross Vs Number Movies')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The plot contains 50 points, one point for each actor in the table. You can see that it slopes upwards, in general. The more movies an actor has been in, the more the total gross of all of those movies – in general.\n",
"\n",
"Formally, we say that the plot shows an *association* between the variables, and that the association is *positive*: high values of one variable tend to be associated with high values of the other, and low values of one with low values of the other, in general. \n",
"\n",
"Of course there is some variability. Some actors have high numbers of movies but middling total gross receipts. Others have middling numbers of movies but high receipts. That the association is positive is simply a statement about the broad general trend.\n",
"\n",
"Later in the course we will study how to quantify association. For the moment, we will just think about it qualitatively."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we have explored how the number of movies is related to the *total* gross receipt, let's turn our attention to how it is related to the *average* gross receipt per movie."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x = actors['Number of Movies']\n",
"y = actors['Average per Movie']\n",
"\n",
"plt.scatter(x, y, c='blue')\n",
"plt.title('Gross Vs Avg per Movie')\n",
"plt.xlabel('Number of Movies')\n",
"plt.ylabel('Average per Movie')\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is a markedly different picture and shows a *negative* association. In general, the more movies an actor has been in, the *less* the average receipt per movie.\n",
"\n",
"Also, one of the points is quite high and off to the left of the plot. It corresponds to one actor who has a low number of movies and high average per movie. This point is an *outlier*. It lies outside the general range of the data. Indeed, it is quite far from all the other points in the plot."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We will examine the negative association further by looking at points at the right and left ends of the plot. \n",
"\n",
"For the right end, let's zoom in on the main body of the plot by just looking at the portion that doesn't have the outlier."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"no_outlier = actors[actors['Number of Movies'] > 10]\n",
"no_outlier.plot.scatter('Number of Movies', 'Average per Movie') #N.B. a pandas scatterplot\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The negative association is still clearly visible. Let's identify the actors corresponding to the points that lie on the right hand side of the plot where the number of movies is large:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
Actor
\n",
"
Total Gross
\n",
"
Number of Movies
\n",
"
Average per Movie
\n",
"
#1 Movie
\n",
"
Gross
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"
\n",
" \n",
" \n",
"
\n",
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1
\n",
"
Samuel L. Jackson
\n",
"
4772.8
\n",
"
69
\n",
"
69.2
\n",
"
The Avengers
\n",
"
623.4
\n",
"
\n",
"
\n",
"
2
\n",
"
Morgan Freeman
\n",
"
4468.3
\n",
"
61
\n",
"
73.3
\n",
"
The Dark Knight
\n",
"
534.9
\n",
"
\n",
"
\n",
"
19
\n",
"
Robert DeNiro
\n",
"
3081.3
\n",
"
79
\n",
"
39.0
\n",
"
Meet the Fockers
\n",
"
279.3
\n",
"
\n",
"
\n",
"
21
\n",
"
Liam Neeson
\n",
"
2942.7
\n",
"
63
\n",
"
46.7
\n",
"
The Phantom Menace
\n",
"
474.5
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Actor Total Gross Number of Movies Average per Movie \\\n",
"1 Samuel L. Jackson 4772.8 69 69.2 \n",
"2 Morgan Freeman 4468.3 61 73.3 \n",
"19 Robert DeNiro 3081.3 79 39.0 \n",
"21 Liam Neeson 2942.7 63 46.7 \n",
"\n",
" #1 Movie Gross \n",
"1 The Avengers 623.4 \n",
"2 The Dark Knight 534.9 \n",
"19 Meet the Fockers 279.3 \n",
"21 The Phantom Menace 474.5 "
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"actors[actors['Number of Movies'] > 60]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The actor Robert DeNiro has the highest number of movies and the lowest average receipt per movie. Other actors are at points that are not very far away, but DeNiro's is at the extreme end.\n",
"\n",
"To understand the negative association, note that the more movies an actor is in, the more variable those movies might be, in terms of style, genre, and box office draw. For example, an actor might be in some high-grossing action movies or comedies (such as Meet the Fockers), and also in a large number of smaller films that may be excellent but don't draw large crowds. Thus the actor's value of average receipts per movie might be relatively low.\n",
"\n",
"To approach this argument from a different direction, let us now take a look at the outlier."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
Actor
\n",
"
Total Gross
\n",
"
Number of Movies
\n",
"
Average per Movie
\n",
"
#1 Movie
\n",
"
Gross
\n",
"
\n",
" \n",
" \n",
"
\n",
"
14
\n",
"
Anthony Daniels
\n",
"
3162.9
\n",
"
7
\n",
"
451.8
\n",
"
Star Wars: The Force Awakens
\n",
"
936.7
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Actor Total Gross Number of Movies Average per Movie \\\n",
"14 Anthony Daniels 3162.9 7 451.8 \n",
"\n",
" #1 Movie Gross \n",
"14 Star Wars: The Force Awakens 936.7 "
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"actors[actors['Number of Movies'] < 10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As an actor, Anthony Daniels might not have the stature of Robert DeNiro. But his 7 movies had an astonishingly high average receipt of nearly $452$ million dollars per movie.\n",
"\n",
"What were these movies? You might know about the droid C-3PO in Star Wars:\n",
"![C-3PO](../../images/C-3PO_droid.png)\n",
"That's [Anthony Daniels](https://en.wikipedia.org/wiki/Anthony_Daniels) inside the metallic suit. He plays C-3PO.\n",
"\n",
"Mr. Daniels' entire filmography (apart from cameos) consists of movies in the high-grossing Star Wars franchise. That explains both his high average receipt and his low number of movies.\n",
"\n",
"Variables such as genre and production budget have an effect on the association between the number of movies and the average receipt per movie. This example is a reminder that studying the association between two variables often involves understanding other related variables as well. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Line Graphs\n",
"Line graphs are among the most common visualizations and are often used to study chronological trends and patterns.\n",
"\n",
"The table `movies_by_year` contains data on movies produced by U.S. studios in each of the years 1980 through 2015. The columns are:\n",
"\n",
"| **Column** | Content |\n",
"|------------|---------|\n",
"| `Year` | Year |\n",
"| `Total Gross` | Total domestic box office gross, in millions of dollars, of all movies released |\n",
"| `Number of Movies` | Number of movies released |\n",
"| `#1 Movie` | Highest grossing movie |"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
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\n",
" \n",
"
\n",
"
\n",
"
Year
\n",
"
Total Gross
\n",
"
Number of Movies
\n",
"
#1 Movie
\n",
"
\n",
" \n",
" \n",
"
\n",
"
0
\n",
"
2015
\n",
"
11128.5
\n",
"
702
\n",
"
Star Wars: The Force Awakens
\n",
"
\n",
"
\n",
"
1
\n",
"
2014
\n",
"
10360.8
\n",
"
702
\n",
"
American Sniper
\n",
"
\n",
"
\n",
"
2
\n",
"
2013
\n",
"
10923.6
\n",
"
688
\n",
"
Catching Fire
\n",
"
\n",
"
\n",
"
3
\n",
"
2012
\n",
"
10837.4
\n",
"
667
\n",
"
The Avengers
\n",
"
\n",
"
\n",
"
4
\n",
"
2011
\n",
"
10174.3
\n",
"
602
\n",
"
Harry Potter / Deathly Hallows (P2)
\n",
"
\n",
"
\n",
"
5
\n",
"
2010
\n",
"
10565.6
\n",
"
536
\n",
"
Toy Story 3
\n",
"
\n",
"
\n",
"
6
\n",
"
2009
\n",
"
10595.5
\n",
"
521
\n",
"
Avatar
\n",
"
\n",
"
\n",
"
7
\n",
"
2008
\n",
"
9630.7
\n",
"
608
\n",
"
The Dark Knight
\n",
"
\n",
"
\n",
"
8
\n",
"
2007
\n",
"
9663.8
\n",
"
631
\n",
"
Spider-Man 3
\n",
"
\n",
"
\n",
"
9
\n",
"
2006
\n",
"
9209.5
\n",
"
608
\n",
"
Dead Man's Chest
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" Year Total Gross Number of Movies #1 Movie\n",
"0 2015 11128.5 702 Star Wars: The Force Awakens\n",
"1 2014 10360.8 702 American Sniper\n",
"2 2013 10923.6 688 Catching Fire\n",
"3 2012 10837.4 667 The Avengers\n",
"4 2011 10174.3 602 Harry Potter / Deathly Hallows (P2)\n",
"5 2010 10565.6 536 Toy Story 3\n",
"6 2009 10595.5 521 Avatar\n",
"7 2008 9630.7 608 The Dark Knight\n",
"8 2007 9663.8 631 Spider-Man 3\n",
"9 2006 9209.5 608 Dead Man's Chest"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"movies_by_year = pd.read_csv(path_data + 'movies_by_year.csv')\n",
"movies_by_year.head(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The Table method `plot` produces a line graph. Its two arguments are the same as those for `scatter`: first the column on the horizontal axis, then the column on the vertical. Here is a line graph of the number of movies released each year over the years 1980 through 2015."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"#N.B. this is a Pandas plot\n",
"\n",
"movies_by_year.plot('Year', 'Number of Movies')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The graph rises sharply and then has a gentle upwards trend though the numbers vary noticeably from year to year. The sharp rise in the early 1980's is due in part to studios returning to the forefront of movie production after some years of filmmaker driven movies in the 1970's. \n",
"\n",
"Our focus will be on more recent years. In keeping with the theme of movies, the table of rows corresponding to the years 2000 through 2015 have been assigned to the name `century_21`."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"century_21 = movies_by_year[movies_by_year['Year'] > 1999]"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"century_21.plot('Year', 'Number of Movies')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The global financial crisis of 2008 has a visible effect – in 2009 there is a sharp drop in the number of movies released.\n",
"\n",
"The dollar figures, however, didn't suffer much."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
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"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"century_21.plot('Year', 'Total Gross')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The total domestic gross receipt was higher in 2009 than in 2008, even though there was a financial crisis and a much smaller number of movies were released.\n",
"\n",
"One reason for this apparent contradiction is that people tend to go to the movies when there is a recession. [\"In Downturn, Americans Flock to the Movies,\"](http://www.nytimes.com/2009/03/01/movies/01films.html?_r=0) said the New York Times in February 2009. The article quotes Martin Kaplan of the University of Southern California saying, \"People want to forget their troubles, and they want to be with other people.\" When holidays and expensive treats are unaffordable, movies provide welcome entertainment and relief.\n",
"\n",
"In 2009, another reason for high box office receipts was the movie Avatar and its 3D release. Not only was Avatar the \\#1 movie of 2009, it is also by some calculations the second highest grossing movie of all time, as we will see later."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"