INST326 Homework 5

20170711, IMDb and Classes

Below is Homework 5, which focuses on class design for representing objects in the IMDb dataset you used in Homework 4.

You will be graded on the following rubric:

  • Class Design: You will be asked to design classes around the IMDb dataset. Your choice of classes should make sense given what we've learned in class and in the Py3OOP book and should have both attributes and behaviors.
  • Documentation: Your code should be sufficiently documented so as to demonstrate you have an understanding of what your code is doing. This point is especially important if you are citing code from the Internet.
  • Execution: Your code should at least execute. If your code does not run, you will get no points for this criteria.
  • Correctness: Your code should implement the specifications provided correctly.
  • Efficiency: While not a major factor, be prepared to have points counted off if your code is extremely inefficient (e.g., looping through a list without apparent need).

NOTE While you may work in groups to discuss strategies for solving these problems, you are expected to do your own work. Excessive similarity among answers may result in punitive action.

You are provided a file, movie_metadata.csv, that contains data from the Internet Movie Database (IMDb) for around 5,000 movies. This file came from Kaggle's datasets. Use this file to answer the following questions.

Part 1. Object-Oriented Design

Review the header for the movie dataset, and use this data to design a set of classes to model this data.

Identifying Objects

Develop a UML class diagram for at least four classes of objects in the IMDb dataset. Your classes should encapsulate all data contained in the given dataset.

You must include the following two classes:

  • A Movie class
  • An Actor class

NOTE : You can review UML class diagrams here:


For each class of object, include at least four attributes/behaviors (e.g., a Movie class has a title, budget, list of actors, and a content rating).

Class Interactions

For your class diagram, include the relationships among your four classes. Be sure to mark these relationships appropriately as inheritance relationships (outlined triangle arrows), associations (lines with no arrows or -> arrows), composition (solid diamond), or aggregation (outlined diamond).

What to Turn In

You should turn in the class diagram as an image file. You can draw the diagram and take a photo of it, scan the drawing, or use an existing graphic tool like Powerpoint, Word, Keynote, Omnigraffle, or other to construct this diagram.

Save your file as a valid PNG or JPG file named class_diagram.png and include the file in your homework submission.

NOTE: Your class diagram file should be in the same directory as this notebook. If so, you should see a copy of your class diagram below:

Part 2. Implementing Your Classes

In the space below, implement the classes you defined above. Include the following aspects:


For each class of object, create an initializer that sets attributes to reasonable default values and requires initializer arguments for attributes that do not have default values (e.g., actor names or movie titles).

Requirements for Movie Class

  • Your Movie class should include a method/function get_actors() that returns a list of Actor objects containing the actors who starred in the film.

  • Your Movie class should include a method percent_return() that calculates the ratio of gross box office income to the movie's budget.

  • Your Movie class should include a method parse_genre_string() that accepts an argument representing a genre string from the CSV file, parses this genre string into a list of genres, and returns a list of genres contained in this genre string.

  • Your Movie class should include a method __str__() that returns a string containing the movie title, rating, and release year.

Requirements for Actor Class

  • Your Actor class should include an attribute that contains a list of all Movie objects in which the actor has starred.

  • Your Actor class should include a method get_filmography() that returns a list of all Movie objects in which this actor starred.

  • Your Actor class should include a method get_total_gross() that calculates the sum of all movie gross returns in which that actor has starred.

  • Your Actor class should include a method get_mean_gross() that calculates the average of all movie gross returns in which that actor has starred.

  • Your Actor class should include a method get_costars() that returns a list of Actor objects containing actors who have starred in movies with this actor.

  • Your Actor class should include a method __str__() that returns a string containing the actor's name.

In [1]:
# Implement here
class Director:
    def __init__(self, name): = name
        self.directed_movies = set()
        self.facebook_likes = 0
    def get_movies(self):
        return self.directed_movies
class Actor:
    def __init__(self, name): = name
        self.costars = {}
        self.filmography = set()
        self.facebook_likes = 0
    def get_costars(self):
        return self.costars
    def __str__(self):
    def get_filmography(self):
        return self.filmography
    def get_total_gross(self):
        total_gross = 0
        for movie in self.filmography:
            if ( movie.gross != None ):
                total_gross += movie.gross
        return total_gross
    def get_mean_gross(self):
        total = self.get_total_gross()
        return total / len(self.filmography)
class Cast:
    def __init__(self, actors=[]):
        self.actors = set(actors)
    def get_facebook_likes(self):
        likes = 0
        for actor in self.actors:
            likes += actor.facebook_likes
        return likes
class ContentRating:
    def __init__(self, rating):
        self.rating = rating
    def __str__(self):
        return self.rating
class Genre:
    def __init__(self, genre):
        self.genre = genre
    def __str__(self):
        return self.genre
class Language:
    def __init__(self, lang):
        self.language = lang
class Movie:
    def __init__(self, title, rating, year):
        # Set from initializer
        self.movie_title = title
        self.rating = rating
        self.release_year = year
        # Create for setting later
        self.cast = None
        self.director = None
        self.plot_keywords = []
        self.languages = []
        self.genres = []
        self.aspect_ratio = None
        self.budget = None = None
        self.duration = None
        self.facenumber_in_poster = None
        self.gross = None
        self.imdb_score = None
        self.facebook_likes = None
        self.imdb_page = None
        self.num_critics = None
        self.num_users = None
        self.num_voted = None
        self.color = None
    def percent_return(self):
        movie_return = None
        if ( self.gross != None and self.budget != None):
            movie_return = self.gross / self.budget
        return movie_return
    def get_actors(self):
        return self.cast
    def parse_genre_string(self, genre_str):
        genres = []
        for g in genre_str.split("|"):
            genre = Genre(g)
        return genres
    def parse_plot_string(self, plot_str):
        plots = []
        for g in plot_str.split("|"):
        return plots
    def __str__(self):
        return "%s, %s, %s" % (self.movie_title, self.rating, self.release_year)


Part 3. Read a List of Movies

Write code below that reads the movie metadata file and populates lists of Movie and Actor objects.

In [2]:
# Implement here
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd

# Read data into data frame, dropping rows with not-a-number values
df = pd.read_csv("movie_metadata.csv", header=0).dropna(axis=0)

# Maps for storing actors, directors, and movies by name
director_map = {}
actor_map = {}
movie_list = []
for row in df.itertuples(False):
    # Create rating
    rating = ContentRating(row.content_rating)
    # Create language
    language = Language(row.language)
    # Create the movie
    this_movie = Movie(row.movie_title, row.title_year, rating)
    this_movie.aspect_ratio = row.aspect_ratio
    this_movie.budget = row.budget =
    this_movie.duration = row.duration
    this_movie.facenumber_in_poster = row.facenumber_in_poster
    this_movie.facebook_likes = row.movie_facebook_likes
    this_movie.gross = row.gross
    this_movie.imdb_score = row.imdb_score
    this_movie.imdb_page = row.movie_imdb_link
    this_movie.num_critics = row.num_critic_for_reviews
    this_movie.num_users = row.num_user_for_reviews
    this_movie.num_voted = row.num_voted_users
    this_movie.color = row.color
    # Parse plot keywords
    this_movie.plot_keywords = this_movie.parse_plot_string(row.plot_keywords)
    # Parse genres
    this_movie.genres = this_movie.parse_genre_string(row.genres)
    # Get director or create if necessary
    director = None
    if ( row.director_name not in director_map ):
        director = Director(row.director_name)
        director = director_map[row.director_name]
    director.facebook_likes = row.director_facebook_likes
    this_movie.director = director
    # Pull actor from map or create if new
    actor1 = None
    if ( row.actor_1_name not in actor_map ):
        actor1 = Actor(row.actor_1_name)
        actor1 = actor_map[row.actor_1_name]
    actor1.facebook_likes = row.actor_1_facebook_likes
    # Pull actor from map or create if new    
    actor2 = None
    if ( row.actor_2_name not in actor_map ):
        actor2 = Actor(row.actor_2_name)
        actor2 = actor_map[row.actor_2_name]
    actor2.facebook_likes = row.actor_2_facebook_likes
    # Pull actor from map or create if new
    actor3 = None
    if ( row.actor_3_name not in actor_map ):
        actor3 = Actor(row.actor_3_name)
        actor3 = actor_map[row.actor_3_name]
    actor3.facebook_likes = row.actor_3_facebook_likes
    # Add costars
    actor_list = [actor1, actor2, actor3]
    for i in range(3):
        if ( actor_list[i].name not in actor_map ):
            actor_map[actor_list[i].name] = actor_list[i]
        for j in range(3):
            if ( i == j ):
            if ( actor_list[j].name not in actor_list[i].costars ):
                actor_list[i].costars[actor_list[j].name] = actor_list[j]
    # Create cast
    cast = Cast(actor_list)
    this_movie.cast = cast


Part 4. Use Your Code

Use your code to answer the following two questions:

  1. Find the movie with the highest ratio of gross to budget, and print its title, genres, starring actors, director, and release year.

  2. Find the actor with highest average movie gross, and print his/her name, filmography, and costars. Use the __str__() methods of Actor and Movie classes to print this data.

In [3]:
# Implement here
max_return = 0
max_movie = None
for movie in movie_list:
    if ( movie.percent_return() > max_return ):
        max_movie = movie
        max_return = movie.percent_return()
print("Movie with highest return:", max_movie.__str__(), max_movie.percent_return())
print("Directed By:",
print("Genres:", ", ".join([g.genre for g in max_movie.genres]))
for actor in max_movie.cast.actors:
Movie with highest return: Paranormal Activity , 2007.0, R 7194.48553333
Directed By: Oren Peli
Genres: Horror
	 Amber Armstrong
	 Ashley Palmer
	 Micah Sloat
In [4]:
max_mean_gross = 0
max_actor = None
for actor in actor_map.values():
    if ( actor.get_mean_gross() > max_mean_gross ):
        max_mean_gross = actor.get_mean_gross()
        max_actor = actor
print("Actor with highest average gross:", max_actor, max_actor.get_mean_gross())
for film in max_actor.filmography:
    print("\t", film)
for actor in max_actor.costars:
    print("\t", actor)
Actor with highest average gross: Gloria Stuart 658672302.0
	 Titanic , 1997.0, PG-13
	 Leonardo DiCaprio
	 Kate Winslet
In [5]:
max_total_gross = 0
max_actor = None
for actor in actor_map.values():
    if ( actor.get_total_gross() > max_total_gross ):
        max_total_gross = actor.get_total_gross()
        max_actor = actor
print("Actor with highest total gross:", max_actor, max_actor.get_total_gross())
for film in max_actor.filmography:
    print("\t", film)
for actor in max_actor.costars:
    print("\t", actor)
Actor with highest total gross: Robert Downey Jr. 4162540754.0
	 Richard III , 1995.0, R
	 Fur: An Imaginary Portrait of Diane Arbus , 2006.0, R
	 Iron Man , 2008.0, PG-13
	 Iron Man 2 , 2010.0, PG-13
	 The Singing Detective , 2003.0, R
	 Iron Man 3 , 2013.0, PG-13
	 Due Date , 2010.0, R
	 Sherlock Holmes: A Game of Shadows , 2011.0, PG-13
	 A Scanner Darkly , 2006.0, R
	 Wonder Boys , 2000.0, R
	 Captain America: Civil War , 2016.0, PG-13
	 Home for the Holidays , 1995.0, PG-13
	 Zodiac , 2007.0, R
	 Bowfinger , 1999.0, PG-13
	 The Soloist , 2009.0, PG-13
	 In Dreams , 1999.0, R
	 The Shaggy Dog , 2006.0, PG
	 Charlie Bartlett , 2007.0, R
	 Tropic Thunder , 2008.0, R
	 The Avengers , 2012.0, PG-13
	 Avengers: Age of Ultron , 2015.0, PG-13
	 Kiss Kiss Bang Bang , 2005.0, R
	 Sherlock Holmes , 2009.0, PG-13
	 Lucky You , 2007.0, PG-13
	 Good Night, and Good Luck. , 2005.0, PG
	 Two Girls and a Guy , 1997.0, R
	 Gothika , 2003.0, R
	 The Avengers , 2012.0, PG-13
	 The Judge , 2014.0, R
	 Chris Hemsworth
	 Scarlett Johansson
	 Chris Evans
	 Jon Favreau
	 Don Cheadle
	 Jeff Bridges
	 Eddie Marsan
	 Paul Anderson
	 Steve Coogan
	 Brandon T. Jackson
	 Robert Maillet
	 Jake Gyllenhaal
	 Anthony Edwards
	 Matt Walsh
	 Joel David Moore
	 Kristin Davis
	 Stephen Root
	 Rachael Harris
	 Adam Alexi-Malle
	 Jamie Kennedy
	 Robert Duvall
	 Kelvin Han Yee
	 Leighton Meester
	 Charles S. Dutton
	 Bernard Hill
	 Rip Torn
	 Richard Thomas
	 Aidan Quinn
	 Paul Guilfoyle
	 Holly Hunter
	 Steve Guttenberg
	 Keanu Reeves
	 Rory Cochrane
	 Ty Burrell
	 Matt Servitto
	 Corbin Bernsen
	 Larry Miller
	 Megan Park
	 Hope Davis
	 Jim Broadbent
	 Kristin Scott Thomas
	 Robin Wright
	 Alfre Woodard
	 Tate Donovan
	 Alex Borstein
	 Natasha Gregson Wagner
	 Angel David
In [6]:
{'CCH Pounder': <__main__.Actor at 0x1147bd7f0>,
 'Joel David Moore': <__main__.Actor at 0x1147bd828>,
 'Wes Studi': <__main__.Actor at 0x1147bd860>,
 'Johnny Depp': <__main__.Actor at 0x1147bdb38>,
 'Orlando Bloom': <__main__.Actor at 0x1147bdb70>,
 'Jack Davenport': <__main__.Actor at 0x1147bdba8>,
 'Christoph Waltz': <__main__.Actor at 0x1147bde80>,
 'Rory Kinnear': <__main__.Actor at 0x1147bdeb8>,
 'Stephanie Sigman': <__main__.Actor at 0x1147bdef0>,
 'Tom Hardy': <__main__.Actor at 0x1147c1128>,
 'Christian Bale': <__main__.Actor at 0x1147c1160>,
 'Joseph Gordon-Levitt': <__main__.Actor at 0x1147c1198>,
 'Daryl Sabara': <__main__.Actor at 0x1147c1470>,
 'Samantha Morton': <__main__.Actor at 0x1147c14a8>,
 'Polly Walker': <__main__.Actor at 0x1147c14e0>,
 'J.K. Simmons': <__main__.Actor at 0x1147c17f0>,
 'James Franco': <__main__.Actor at 0x1147c1828>,
 'Kirsten Dunst': <__main__.Actor at 0x1147c1860>,
 'Brad Garrett': <__main__.Actor at 0x1147c1cf8>,
 'Donna Murphy': <__main__.Actor at 0x1147c1d30>,
 'M.C. Gainey': <__main__.Actor at 0x1147c1d68>,
 'Chris Hemsworth': <__main__.Actor at 0x1147c1fd0>,
 'Robert Downey Jr.': <__main__.Actor at 0x1147c4048>,
 'Scarlett Johansson': <__main__.Actor at 0x1147c4080>,
 'Alan Rickman': <__main__.Actor at 0x1147c4438>,
 'Daniel Radcliffe': <__main__.Actor at 0x1147c4470>,
 'Rupert Grint': <__main__.Actor at 0x11182dcc0>,
 'Henry Cavill': <__main__.Actor at 0x10b6363c8>,
 'Lauren Cohan': <__main__.Actor at 0x10b636390>,
 'Alan D. Purwin': <__main__.Actor at 0x10b636400>,
 'Kevin Spacey': <__main__.Actor at 0x10b6369e8>,
 'Marlon Brando': <__main__.Actor at 0x10b636c18>,
 'Frank Langella': <__main__.Actor at 0x10b636b70>,
 'Giancarlo Giannini': <__main__.Actor at 0x11466e320>,
 'Mathieu Amalric': <__main__.Actor at 0x11466e400>,
 'Ruth Wilson': <__main__.Actor at 0x1147c4780>,
 'Tom Wilkinson': <__main__.Actor at 0x1147c47b8>,
 'Christopher Meloni': <__main__.Actor at 0x1147c4ac8>,
 'Harry Lennix': <__main__.Actor at 0x1147c4b00>,
 'Peter Dinklage': <__main__.Actor at 0x1147c4e48>,
 'Pierfrancesco Favino': <__main__.Actor at 0x1147c4e80>,
 'Damián Alcázar': <__main__.Actor at 0x1147c4eb8>,
 'Sam Claflin': <__main__.Actor at 0x1147c84e0>,
 'Stephen Graham': <__main__.Actor at 0x1147c8518>,
 'Will Smith': <__main__.Actor at 0x1147c8978>,
 'Michael Stuhlbarg': <__main__.Actor at 0x1147c89b0>,
 'Nicole Scherzinger': <__main__.Actor at 0x1147c89e8>,
 'Aidan Turner': <__main__.Actor at 0x1147c8cc0>,
 'Adam Brown': <__main__.Actor at 0x1147c8cf8>,
 'James Nesbitt': <__main__.Actor at 0x1147c8d30>,
 'Emma Stone': <__main__.Actor at 0x1147cd080>,
 'Andrew Garfield': <__main__.Actor at 0x1147cd0b8>,
 'Chris Zylka': <__main__.Actor at 0x1147cd0f0>,
 'Mark Addy': <__main__.Actor at 0x1147cd470>,
 'William Hurt': <__main__.Actor at 0x1147cd4a8>,
 'Scott Grimes': <__main__.Actor at 0x1147cd4e0>,
 'Christopher Lee': <__main__.Actor at 0x1147cda58>,
 'Eva Green': <__main__.Actor at 0x1147cda90>,
 'Kristin Scott Thomas': <__main__.Actor at 0x1147cdac8>,
 'Naomi Watts': <__main__.Actor at 0x1147cde10>,
 'Thomas Kretschmann': <__main__.Actor at 0x1147cde48>,
 'Evan Parke': <__main__.Actor at 0x1147cde80>,
 'Leonardo DiCaprio': <__main__.Actor at 0x1147cf208>,
 'Kate Winslet': <__main__.Actor at 0x1147cf240>,
 'Gloria Stuart': <__main__.Actor at 0x1147cf278>,
 'Chris Evans': <__main__.Actor at 0x1147cf518>,
 'Liam Neeson': <__main__.Actor at 0x1147cf860>,
 'Alexander Skarsgård': <__main__.Actor at 0x1147cf898>,
 'Tadanobu Asano': <__main__.Actor at 0x1147cf8d0>,
 'Bryce Dallas Howard': <__main__.Actor at 0x1147cfb70>,
 'Judy Greer': <__main__.Actor at 0x1147cfba8>,
 'Omar Sy': <__main__.Actor at 0x1147cfbe0>,
 'Albert Finney': <__main__.Actor at 0x1147cfe48>,
 'Helen McCrory': <__main__.Actor at 0x1147cfe80>,
 'Jon Favreau': <__main__.Actor at 0x113b13470>,
 'Don Cheadle': <__main__.Actor at 0x113b134a8>,
 'Anne Hathaway': <__main__.Actor at 0x113b13748>,
 'Hugh Jackman': <__main__.Actor at 0x113b13b38>,
 'Kelsey Grammer': <__main__.Actor at 0x113b13b70>,
 'Daniel Cudmore': <__main__.Actor at 0x113b13ba8>,
 'Steve Buscemi': <__main__.Actor at 0x113b13ef0>,
 'Tyler Labine': <__main__.Actor at 0x113b13f28>,
 'Sean Hayes': <__main__.Actor at 0x113b13f60>,
 'Glenn Morshower': <__main__.Actor at 0x113b162e8>,
 'Kevin Dunn': <__main__.Actor at 0x113b16320>,
 'Ramon Rodriguez': <__main__.Actor at 0x113b16358>,
 'Bingbing Li': <__main__.Actor at 0x113b16630>,
 'Sophia Myles': <__main__.Actor at 0x113b16668>,
 'Tim Holmes': <__main__.Actor at 0x113b169b0>,
 'Mila Kunis': <__main__.Actor at 0x113b169e8>,
 'B.J. Novak': <__main__.Actor at 0x113b16cc0>,
 'Jeff Bridges': <__main__.Actor at 0x113b1a048>,
 'Olivia Wilde': <__main__.Actor at 0x113b1a080>,
 'James Frain': <__main__.Actor at 0x113b1a0b8>,
 'Joe Mantegna': <__main__.Actor at 0x113b1a400>,
 'Eddie Izzard': <__main__.Actor at 0x113b1a438>,
 'Ryan Reynolds': <__main__.Actor at 0x113b1a780>,
 'Temuera Morrison': <__main__.Actor at 0x113b1a7b8>,
 'Taika Waititi': <__main__.Actor at 0x113b1a7f0>,
 'Tom Hanks': <__main__.Actor at 0x113b1aba8>,
 'John Ratzenberger': <__main__.Actor at 0x113b1abe0>,
 'Don Rickles': <__main__.Actor at 0x113b1ac18>,
 'Common': <__main__.Actor at 0x113b1af60>,
 'Jason Statham': <__main__.Actor at 0x113b1e240>,
 'Paul Walker': <__main__.Actor at 0x113b1e278>,
 'Vin Diesel': <__main__.Actor at 0x113b1e2b0>,
 'Peter Capaldi': <__main__.Actor at 0x113b1e668>,
 'Brad Pitt': <__main__.Actor at 0x113b1e6a0>,
 'Mireille Enos': <__main__.Actor at 0x113b1e6d8>,
 'Jennifer Lawrence': <__main__.Actor at 0x113b1e9e8>,
 'Benedict Cumberbatch': <__main__.Actor at 0x113b1ed68>,
 'Bruce Greenwood': <__main__.Actor at 0x113b1eda0>,
 'Noel Clarke': <__main__.Actor at 0x113b1edd8>,
 'Eddie Marsan': <__main__.Actor at 0x113b230b8>,
 'Ewen Bremner': <__main__.Actor at 0x113b230f0>,
 'Ralph Brown': <__main__.Actor at 0x113b23128>,
 'Elizabeth Debicki': <__main__.Actor at 0x113b23400>,
 'Steve Bisley': <__main__.Actor at 0x113b23438>,
 'Jake Gyllenhaal': <__main__.Actor at 0x113b237f0>,
 'Richard Coyle': <__main__.Actor at 0x113b23828>,
 'Reece Ritchie': <__main__.Actor at 0x113b23860>,
 'Charlie Hunnam': <__main__.Actor at 0x113b23ba8>,
 'Clifton Collins Jr.': <__main__.Actor at 0x113b23be0>,
 'Larry Joe Campbell': <__main__.Actor at 0x113b23c18>,
 'Lester Speight': <__main__.Actor at 0x113b23ef0>,
 'Harrison Ford': <__main__.Actor at 0x113b28198>,
 'Ray Winstone': <__main__.Actor at 0x113b281d0>,
 'Jim Broadbent': <__main__.Actor at 0x113b28208>,
 'Kelly Macdonald': <__main__.Actor at 0x113b28550>,
 'Julie Walters': <__main__.Actor at 0x113b28588>,
 'Sofia Boutella': <__main__.Actor at 0x113b28898>,
 'Melissa Roxburgh': <__main__.Actor at 0x113b288d0>,
 'Lydia Wilson': <__main__.Actor at 0x113b28908>,
 'Fred Willard': <__main__.Actor at 0x113b28cc0>,
 'Jeff Garlin': <__main__.Actor at 0x113b28cf8>,
 'Tzi Ma': <__main__.Actor at 0x113b2d0b8>,
 'Dana Ivey': <__main__.Actor at 0x113b2d0f0>,
 'Noémie Lenoir': <__main__.Actor at 0x113b2d128>,
 'Oliver Platt': <__main__.Actor at 0x113b2d400>,
 'Liam James': <__main__.Actor at 0x113b2d438>,
 'Tom McCarthy': <__main__.Actor at 0x113b2d470>,
 'Robin Wright': <__main__.Actor at 0x113b2d7b8>,
 'Colin Firth': <__main__.Actor at 0x113b2d7f0>,
 'Gary Oldman': <__main__.Actor at 0x113b2d828>,
 'Channing Tatum': <__main__.Actor at 0x113b2da90>,
 'Eddie Redmayne': <__main__.Actor at 0x113b2dac8>,
 'Casper Crump': <__main__.Actor at 0x113b2de80>,
 'Kiran Shah': <__main__.Actor at 0x113b311d0>,
 'Shane Rangi': <__main__.Actor at 0x113b31208>,
 'Michael Fassbender': <__main__.Actor at 0x113b314e0>,
 'Tye Sheridan': <__main__.Actor at 0x113b31518>,
 'Heath Ledger': <__main__.Actor at 0x113b317f0>,
 'Morgan Freeman': <__main__.Actor at 0x113b31828>,
 'Delroy Lindo': <__main__.Actor at 0x113b31b70>,
 'Jess Harnell': <__main__.Actor at 0x113b31ba8>,
 'Amy Poehler': <__main__.Actor at 0x113b31f98>,
 'Rainn Wilson': <__main__.Actor at 0x113b31fd0>,
 'Stephen Colbert': <__main__.Actor at 0x113b36048>,
 'Chloë Grace Moretz': <__main__.Actor at 0x113b365c0>,
 'Salma Hayek': <__main__.Actor at 0x113b36940>,
 'Bai Ling': <__main__.Actor at 0x113b36978>,
 'Jet Li': <__main__.Actor at 0x113b36d68>,
 'Brendan Fraser': <__main__.Actor at 0x113b36da0>,
 'Russell Wong': <__main__.Actor at 0x113b36dd8>,
 'Robin Atkin Downes': <__main__.Actor at 0x113b3b0f0>,
 'Ike Barinholtz': <__main__.Actor at 0x113b3b128>,
 'Jimmy Bennett': <__main__.Actor at 0x113b3b470>,
 'Steve Carell': <__main__.Actor at 0x113b3b4a8>,
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 'Eve': <__main__.Actor at 0x11451aa58>,
 'Leila Arcieri': <__main__.Actor at 0x11451aa90>,
 'Tim Conway': <__main__.Actor at 0x11451ae48>,
 'Billy West': <__main__.Actor at 0x11451ae80>,
 'John Amos': <__main__.Actor at 0x114520cc0>,
 'Franco Nero': <__main__.Actor at 0x114520cf8>,
 'Josh Charles': <__main__.Actor at 0x114523080>,
 'Freddy Rodríguez': <__main__.Actor at 0x114523780>,
 'Bob Balaban': <__main__.Actor at 0x1145237b8>,
 'Raoul Bova': <__main__.Actor at 0x114523b00>,
 'Bridgit Mendler': <__main__.Actor at 0x114523eb8>,
 'Chris Klein': <__main__.Actor at 0x1145282b0>,
 'Radha Mitchell': <__main__.Actor at 0x1145284a8>,
 'LeVar Burton': <__main__.Actor at 0x1145287f0>,
 'Jonathan Frakes': <__main__.Actor at 0x114528828>,
 'Michael Dorn': <__main__.Actor at 0x114528860>,
 'Alison Lohman': <__main__.Actor at 0x114528d68>,
 'David Hyde Pierce': <__main__.Actor at 0x11452e0f0>,
 'Peter Gerety': <__main__.Actor at 0x11452e128>,
 'Ron Rifkin': <__main__.Actor at 0x11452e160>,
 'Jeremy Irvine': <__main__.Actor at 0x11452e438>,
 'Todd Graff': <__main__.Actor at 0x11452e9b0>,
 'John Buffalo Mailer': <__main__.Actor at 0x11452ec18>,
 'Sarah Gadon': <__main__.Actor at 0x114532080>,
 'Zach McGowan': <__main__.Actor at 0x1145320b8>,
 'Mark Valley': <__main__.Actor at 0x1145322b0>,
 'Nathaniel Parker': <__main__.Actor at 0x114532668>,
 'Victor Wong': <__main__.Actor at 0x1145329e8>,
 'Chelcie Ross': <__main__.Actor at 0x114532c88>,
 'Brooke Smith': <__main__.Actor at 0x114532f98>,
 'Garcelle Beauvais': <__main__.Actor at 0x114532fd0>,
 'Ben Daniels': <__main__.Actor at 0x1145382e8>,
 'Dexter Fletcher': <__main__.Actor at 0x114538320>,
 'Phill Lewis': <__main__.Actor at 0x114538668>,
 'Tate Taylor': <__main__.Actor at 0x1145386a0>,
 'Stephen Rea': <__main__.Actor at 0x1145389b0>,
 'Sandrine Holt': <__main__.Actor at 0x1145389e8>,
 'James Martin Kelly': <__main__.Actor at 0x114538da0>,
 'Shane Hartline': <__main__.Actor at 0x114538dd8>,
 'Celina Beach': <__main__.Actor at 0x114538e10>,
 'Rory Cochrane': <__main__.Actor at 0x11453c160>,
 'Talisa Soto': <__main__.Actor at 0x11453cac8>,
 'Gregg Henry': <__main__.Actor at 0x11453cb00>,
 'Minnie Driver': <__main__.Actor at 0x11453cef0>,
 'Ron Howard': <__main__.Actor at 0x114541400>,
 'Brandy Norwood': <__main__.Actor at 0x114541438>,
 'Archie Kao': <__main__.Actor at 0x1145417f0>,
 'Brandon Molale': <__main__.Actor at 0x114541828>,
 'Laurence Olivier': <__main__.Actor at 0x114541be0>,
 'Charlotte Rampling': <__main__.Actor at 0x114541ef0>,
 'Indira Varma': <__main__.Actor at 0x114541f28>,
 'Neil Maskell': <__main__.Actor at 0x114541f60>,
 '50 Cent': <__main__.Actor at 0x1145453c8>,
 'Matt Gerald': <__main__.Actor at 0x114545400>,
 'Roxanne McKee': <__main__.Actor at 0x1145456d8>,
 'Luke Newberry': <__main__.Actor at 0x114545710>,
 'Gaia Weiss': <__main__.Actor at 0x114545748>,
 'Philip Baker Hall': <__main__.Actor at 0x114545a58>,
 'Gary Farmer': <__main__.Actor at 0x11454a0f0>,
 'Vincent Pastore': <__main__.Actor at 0x11454a7f0>,
 'Robert Blake': <__main__.Actor at 0x11454a828>,
 'Aida Turturro': <__main__.Actor at 0x11454a860>,
 'Max Minghella': <__main__.Actor at 0x11454ae10>,
 'Ashraf Barhom': <__main__.Actor at 0x11454ae48>,
 'Rupert Evans': <__main__.Actor at 0x11454ae80>,
 'Jenna Fischer': <__main__.Actor at 0x11454f4a8>,
 'Stephen Merchant': <__main__.Actor at 0x11454f4e0>,
 'Simon McBurney': <__main__.Actor at 0x11454fa58>,
 'Michael Gaston': <__main__.Actor at 0x11454fa90>,
 'Kevin McNally': <__main__.Actor at 0x114556080>,
 'Maury Chaykin': <__main__.Actor at 0x1145560b8>,
 'Mitch Pileggi': <__main__.Actor at 0x114556470>,
 'Owen Teale': <__main__.Actor at 0x1145567f0>,
 'Lisa Edelstein': <__main__.Actor at 0x11455b048>,
 'Reece Thompson': <__main__.Actor at 0x11455b748>,
 'Marcus Chong': <__main__.Actor at 0x11455bc88>,
 'Gloria Foster': <__main__.Actor at 0x11455bcc0>,
 'Miko Hughes': <__main__.Actor at 0x11455bf60>,
 'Kathleen Quinlan': <__main__.Actor at 0x11455bf98>,
 'Judge Reinhold': <__main__.Actor at 0x11455f550>,
 'Aisha Tyler': <__main__.Actor at 0x11455f588>,
 'Eric Lloyd': <__main__.Actor at 0x11455f5c0>,
 'Jean Stapleton': <__main__.Actor at 0x11455fb38>,
 'Andrea Savage': <__main__.Actor at 0x11455fda0>,
In [12]:
with open("adj.csv", "w") as out_file:
    for _,actor in actor_map.items():
        adj = [(, for x in actor.costars.values()]
        for tup in adj:
            out_file.write("%s,%s\n" % tup)
In [ ]: