Name: The Movies Dataset
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

The Movies Dataset

Context

These files contain metadata for all 45,000 movies listed in the Full MovieLens Dataset. The dataset consists of movies released on or before July 2017. Data points include cast, crew, plot keywords, budget, revenue, posters, release dates, languages, production companies, countries, TMDB vote counts and vote averages.

This dataset also has files containing 26 million ratings from 270,000 users for all 45,000 movies. Ratings are on a scale of 1-5 and have been obtained from the official GroupLens website.

Content

This dataset consists of the following files:

movies_metadata.csv: The main Movies Metadata file. Contains information on 45,000 movies featured in the Full MovieLens dataset. Features include posters, backdrops, budget, revenue, release dates, languages, production countries and companies.

keywords.csv: Contains the movie plot keywords for our MovieLens movies. Available in the form of a stringified JSON Object.

credits.csv: Consists of Cast and Crew Information for all our movies. Available in the form of a stringified JSON Object.

links.csv: The file that contains the TMDB and IMDB IDs of all the movies featured in the Full MovieLens dataset.

links_small.csv: Contains the TMDB and IMDB IDs of a small subset of 9,000 movies of the Full Dataset.

ratings_small.csv: The subset of 100,000 ratings from 700 users on 9,000 movies.

The Full MovieLens Dataset consisting of 26 million ratings and 750,000 tag applications from 270,000 users on all the 45,000 movies in this dataset can be accessed here

Acknowledgements

This dataset is an ensemble of data collected from TMDB and GroupLens.
The Movie Details, Credits and Keywords have been collected from the TMDB Open API. This product uses the TMDb API but is not endorsed or certified by TMDb. Their API also provides access to data on many additional movies, actors and actresses, crew members, and TV shows. You can try it for yourself here.

The Movie Links and Ratings have been obtained from the Official GroupLens website. The files are a part of the dataset available here

Inspiration

This dataset was assembled as part of my second Capstone Project for Springboard's Data Science Career Track. I wanted to perform an extensive EDA on Movie Data to narrate the history and the story of Cinema and use this metadata in combination with MovieLens ratings to build various types of Recommender Systems.

Both my notebooks are available as kernels with this dataset: The Story of Film and Movie Recommender Systems

Some of the things you can do with this dataset:
Predicting movie revenue and/or movie success based on a certain metric. What movies tend to get higher vote counts and vote averages on TMDB? Building Content Based and Collaborative Filtering Based Recommendation Engines.

Tables

Credits

@kaggle.rounakbanik_the_movies_dataset.credits

65.29 MB
45476 rows
3 columns


CREATE TABLE credits (
  "cast" VARCHAR,
  "crew" VARCHAR,
  "id" BIGINT
);

Keywords

@kaggle.rounakbanik_the_movies_dataset.keywords

2.31 MB
46419 rows
2 columns


CREATE TABLE keywords (
  "id" BIGINT,
  "keywords" VARCHAR
);

Links

@kaggle.rounakbanik_the_movies_dataset.links

890.47 KB
45843 rows
3 columns


CREATE TABLE links (
  "movieid" BIGINT,
  "imdbid" BIGINT,
  "tmdbid" DOUBLE
);

Links Small

@kaggle.rounakbanik_the_movies_dataset.links_small

169.97 KB
9125 rows
3 columns


CREATE TABLE links_small (
  "movieid" BIGINT,
  "imdbid" BIGINT,
  "tmdbid" DOUBLE
);

Movies Metadata

@kaggle.rounakbanik_the_movies_dataset.movies_metadata

16.43 MB
45466 rows
24 columns


CREATE TABLE movies_metadata (
  "adult" VARCHAR,
  "belongs_to_collection" VARCHAR,
  "budget" VARCHAR,
  "genres" VARCHAR,
  "homepage" VARCHAR,
  "id" VARCHAR,
  "imdb_id" VARCHAR,
  "original_language" VARCHAR,
  "original_title" VARCHAR,
  "overview" VARCHAR,
  "popularity" VARCHAR,
  "poster_path" VARCHAR,
  "production_companies" VARCHAR,
  "production_countries" VARCHAR,
  "release_date" VARCHAR,
  "revenue" DOUBLE,
  "runtime" DOUBLE,
  "spoken_languages" VARCHAR,
  "status" VARCHAR,
  "tagline" VARCHAR,
  "title" VARCHAR,
  "video" VARCHAR,
  "vote_average" DOUBLE,
  "vote_count" DOUBLE
);

Ratings

@kaggle.rounakbanik_the_movies_dataset.ratings

160.82 MB
26024289 rows
4 columns


CREATE TABLE ratings (
  "userid" BIGINT,
  "movieid" BIGINT,
  "rating" DOUBLE,
  "timestamp" BIGINT
);

Ratings Small

@kaggle.rounakbanik_the_movies_dataset.ratings_small

803.48 KB
100004 rows
4 columns


CREATE TABLE ratings_small (
  "userid" BIGINT,
  "movieid" BIGINT,
  "rating" DOUBLE,
  "timestamp" BIGINT
);