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The Next Bechdel Test: nextBechdel_allTests.csv

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This table contains data behind the story The Next Bechdel Test.

nextBechal_allTests.csv and shows the high-level breakdown of which movies passed and failed - Each row is one of the 50 top-grossing movies from 2016. - Each column is one of the tests. A 0 means the movie failed that test, a 1 means it passed.

nextBechal_castGender.csv contains the estimated gender for the entire cast for every movie, including whether a role was supporting or main. Data was obtained from The Numbers.

Variable Definition
MOVIE Title of the film
ACTOR Full name of the actor
CHARACTER All characters played by the actor in that movie
TYPE Leading, Supporting, Cameo or Lead Ensemble Member
BILLING Billing number
GENDER Estimated gender of the actor

nextBechal_crewGender.csv contains data for the crew for every movie, by probablity that a give first name is male.

Variable Definition
MOVIE Title of the film
DEPARTMENT Full name of the actor
FULL_NAME Actor's first and last name
FIRST_NAME Just first name of actor
IMDB Actor's IMDB page
GENDER_PROB Percent chance that a given name is male
GENDER_GUESS Based on the probablity, guess if the name is male or female

Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub · About: simonw/fivethirtyeight-datasette

50 rows sorted by ko

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This data as json, copyable, CSV (advanced)

Suggested facets: bechdel, peirce, landau, feldman, villareal, hagen, ko, waithe, koeze_dottle, rees-davies

Link rowid movie bechdel peirce landau feldman villareal hagen ko ▼ villarobos waithe koeze_dottle uphold white rees-davies
1 1 Bad Moms 0 0 0 1 0 0 0 1 0 0 1 1 1
2 2 Hidden Figures 0 0 0 0 0 1 0 1 0 1 1 1 1
3 3 Independence Day: Resurgence 0 0 1 0 0 1 0 1 0 0 1 1 1
5 5 Ghostbusters 0 0 0 0 0 1 0 1 1 1 1 1 1
6 6 Allegiant 0 0 1 0 0 1 0 1 1 1 1 1 1
8 8 Ice Age: Collision Course 0 1 0 1 1 1 0 1 1 0 1 1 0
9 9 Kung Fu Panda 3 0 1 0 0 1 1 0 1 1 1 1 1 0
11 11 Sing 0 0 1 1 1 1 0 1 1 0 1 1 0
14 14 Boo! A Madea Halloween 0 0 1 1 1 1 0 1 0 0 1 1 1
16 16 Fantastic Beasts and Where to Find Them 0 0 1 1 0 1 0 1 1 1 1 1 1
18 18 Now You See Me 2 1 0 0 1 0 1 0 1 1 1 1 1 1
21 21 Sausage Party 0 0 1 1 1 1 0 1 1 1 1 1 0
23 23 Suicide Squad 0 0 1 1 1 1 0 1 1 1 1 1 0
25 25 The Purge: Election Year 0 0 1 1 0 1 0 1 1 1 1 1 1
30 30 Central Intelligence 1 0 1 1 1 1 0 1 0 1 1 1 1
34 34 Moana 0 0 1 1 1 1 0 1 1 1 1 1 1
35 35 Ride Along 2 1 0 0 1 1 1 0 1 1 1 1 1 1
36 36 Star Trek Beyond 1 0 1 1 1 1 0 1 1 1 1 1 0
39 39 The Angry Birds Movie 1 1 0 1 0 1 0 1 1 1 1 1 1
45 45 The Accountant 1 0 1 1 1 1 0 1 1 1 1 1 1
46 46 The Jungle Book 1 1 0 1 1 1 0 1 1 1 1 1 1
4 4 Finding Dory 0 0 1 0 0 0 1 1 1 1 1 1 0
7 7 Arrival 0 0 1 0 0 1 1 1 1 0 1 1 1
10 10 Miss Peregrine's Home for Peculiar Children 0 0 0 0 0 1 1 1 1 1 1 1 1
12 12 The Boss 0 0 0 0 1 1 1 1 1 0 1 1 1
13 13 The Girl on the Train 0 0 1 0 0 1 1 1 1 0 1 1 1
15 15 Alice Through the Looking Glass 0 0 1 0 1 1 1 1 1 1 1 1 0
17 17 La La Land 0 0 1 1 0 1 1 1 1 0 1 1 1
19 19 Passengers 1 0 0 1 0 1 1 1 1 0 1 1 1
20 20 Pete's Dragon 0 1 1 0 0 1 1 1 1 1 1 1 0
22 22 Storks 1 0 1 1 0 1 1 1 1 0 1 1 0
24 24 The Conjuring 2 0 0 1 1 0 1 1 1 1 0 1 1 1
26 26 X-Men: Apocalypse 0 0 0 1 0 1 1 1 1 1 1 1 1
27 27 10 Cloverfield Lane 0 0 1 1 0 1 1 1 1 1 1 1 1
28 28 Batman v Superman: Dawn of Justice 1 0 1 1 0 1 1 1 1 1 1 1 0
29 29 Captain America: Civil War 0 0 1 1 1 1 1 1 1 1 1 1 0
31 31 Don't Breathe 0 0 1 1 1 1 1 1 1 0 1 1 1
32 32 Hacksaw Ridge 1 1 0 1 0 1 1 1 1 1 1 1 0
33 33 Lights Out 0 0 1 1 1 1 1 1 1 0 1 1 1
37 37 Sully 1 1 0 1 0 1 1 1 1 0 1 1 1
38 38 Teenage Mutant Ninja Turtles: Out of the Shadows 0 1 0 1 0 1 1 1 1 1 1 1 1
40 40 The Magnificent Seven 1 0 0 1 0 1 1 1 1 1 1 1 1
41 41 Trolls 0 0 1 1 1 1 1 1 1 0 1 1 1
42 42 Zootopia 0 0 1 1 0 1 1 1 1 1 1 1 1
43 43 Jason Bourne 1 0 1 1 1 1 1 1 1 1 1 1 0
44 44 Rogue One 0 0 1 1 1 1 1 1 1 1 1 1 1
47 47 The Legend of Tarzan 1 0 1 1 0 1 1 1 1 1 1 1 1
48 48 Deadpool 1 1 1 1 1 1 1 1 1 0 1 1 1
49 49 Doctor Strange 1 1 1 1 1 1 1 1 1 1 1 1 0
50 50 The Secret Life of Pets 1 0 1 1 1 1 1 1 1 1 1 1 1

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CREATE TABLE "next-bechdel/nextBechdel_allTests" (
"movie" TEXT,
  "bechdel" INTEGER,
  "peirce" INTEGER,
  "landau" INTEGER,
  "feldman" INTEGER,
  "villareal" INTEGER,
  "hagen" INTEGER,
  "ko" INTEGER,
  "villarobos" INTEGER,
  "waithe" INTEGER,
  "koeze_dottle" INTEGER,
  "uphold" INTEGER,
  "white" INTEGER,
  "rees-davies" INTEGER
);
Powered by Datasette · Queries took 111.017ms · Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub · About: simonw/fivethirtyeight-datasette