Name: Movie Industry
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Movie Industry

Context

Is the movie industry dying? is Netflix the new entertainment king? Those were the first questions that lead me to create a dataset
focused on movie revenue and analyze it over the last decades. But, why stop there? There are more factors that intervene in this
kind of thing, like actors, genres, user ratings and more. And now, anyone with experience (you) can ask specific questions about the
movie industry, and get answers.

Content

There are 6820 movies in the dataset (220 movies per year, 1986-2016). Each movie has the following attributes:

budget: the budget of a movie. Some movies don't have this, so it appears as 0
company: the production company
country: country of origin
director: the director
genre: main genre of the movie.
gross: revenue of the movie
name: name of the movie
rating: rating of the movie (R, PG, etc.)
released: release date (YYYY-MM-DD)
runtime: duration of the movie
score: IMDb user rating
votes: number of user votes
star: main actor/actress
writer: writer of the movie
year: year of release

Acknowledgements

This data was scraped from IMDb.

Contribute

You can contribute via GitHub.

Tables

Movies

@kaggle.danielgrijalvas_movies.movies

478.04 kB
7,668 rows
15 columns

CREATE TABLE movies (
  "name" VARCHAR,
  "rating" VARCHAR,
  "genre" VARCHAR,
  "year" BIGINT,
  "released" VARCHAR,
  "score" DOUBLE,
  "votes" DOUBLE,
  "director" VARCHAR,
  "writer" VARCHAR,
  "star" VARCHAR,
  "country" VARCHAR,
  "budget" DOUBLE,
  "gross" DOUBLE,
  "company" VARCHAR,
  "runtime" DOUBLE
);