best_picture {ohenery}

Oscar Award Best Picture Data

Description

Historical data on the Best Picture nominees and winners from 1934 through 2014.

Usage

data(best_picture)

Format

A data.frame object with 484 observations and 19 columns. The columns are defined as follows:

year

The integer year of the nomination. These span from 1934 through 2014. Note that the number of films nominated per year varies from 5 to 12.

film

The title of the film.

winner

A logical for whether the film won the Oscar for Best Picture. There is exactly one winning film per year.

nominated_for_Writing

A logical indicating whether the film was also nominated for a Writing award that year.

nominated_for_BestDirector

A logical indicating whether the film was also nominated for Best Director award that year.

nominated_for_BestActress

A logical indicating whether the film was also nominated for at least one Best Actress award that year.

nominated_for_BestActor

A logical indicating whether the film was also nominated for at least one Best Actor award that year.

nominated_for_BestFilmEditing

A logical indicating whether the film was also nominated for at least one Best Film Editing award that year.

Adventure

A double computed as a 0/1 indicator of whether “Adventure” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Biography

A double computed as a 0/1 indicator of whether “Biography” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Comedy

A double computed as a 0/1 indicator of whether “Comedy” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Crime

A double computed as a 0/1 indicator of whether “Crime” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Drama

A double computed as a 0/1 indicator of whether “Drama” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

History

A double computed as a 0/1 indicator of whether “History” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Musical

A double computed as a 0/1 indicator of whether “Musical” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Romance

A double computed as a 0/1 indicator of whether “Romance” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Thriller

A double computed as a 0/1 indicator of whether “Thriller” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

War

A double computed as a 0/1 indicator of whether “War” was one of the genres tagged for the film in IMDb, divided by the total count of genres tagged for the film.

Other

A double computed as 1 minus the sum of the other genre indicators. Effectively this is is the sum of indicators for “Mystery”, “Family”, “Fantasy”, “Action”, “Western”, “Music”, “Sport”, “Sci Fi”, “Film-Noir”, “Animation”, and “Horror” divided by the total count of genres tagged for the film.

Note

“Oscar” is a copyright property of the Academy of Motion Picture Arts and Sciences. IMDb is owned by Amazon.

Author(s)

Steven E. Pav [e-mail]

Source

Awards data were sourced from Wikipedia, while genre data were sourced from IMDb. Any errors in transcription are the fault of the package author.

Examples

library(dplyr)
data(best_picture)

best_picture %>% 
  group_by(nominated_for_BestDirector) %>% 
  summarize(propwin=mean(winner)) %>% 
  ungroup()
best_picture %>% 
  group_by(nominated_for_BestActor) %>% 
  summarize(propwin=mean(winner)) %>% 
  ungroup()
# hmmmm.
best_picture %>% 
  group_by(nominated_for_BestActress) %>% 
  summarize(propwin=mean(winner)) %>% 
 ungroup()