Context

This dataset contains IMDb data in conjunction with descriptions for the titles taken from Rotten Tomatoes.

This data was collected in an attempt to aid my Books dataset to help with projects concerning cross-content analysis/recommendations for instance.

Please Upvote if this helps you!

Content

The most (Total 21 features) prominent features are:

Title Type
Primary Title
Original Title
Is Adult?
Year
Run-time Minutes
Genres (Multiple)
Average Rating (as on IMDb)
Num. of Votes
Region
Genres
Average Rating
Number of Ratings
Types
Attributes
Description

Important Data Context

The initial dataset being too large has been filtered. The following are the criteria for it:

The data is from the 90s and onwards
Only 'en' (English) language titles have been retained
The regions range from Canada, Greater Britain, India and USA Only
Movie/shows from the 90s-00s with ratings greater than or equal to 7.9 have been retained
Movie/shows from the 2000s and onwards with ratings greater than or equal to 6.5 have been retained
Only titles with num of rating votes greater than 3000 have been retained for Canada and India

Inspiration

Cluster movies/shows based on Descriptions and Genres
Content-based recommendation system using Genre, Description, and Ratings
Genre prediction from Description data (Multi-label classification)

Tables

Imdb

@kaggle.ishikajohari_imdb_data_with_descriptions.imdb

2.2 MB
7850 rows
21 columns


CREATE TABLE imdb (
  "unnamed_0" BIGINT,
  "index" BIGINT,
  "tconst" VARCHAR,
  "titletype" VARCHAR,
  "primarytitle" VARCHAR,
  "originaltitle" VARCHAR,
  "isadult" BIGINT,
  "startyear" BIGINT,
  "endyear" VARCHAR,
  "runtimeminutes" VARCHAR,
  "genres" VARCHAR,
  "averagerating" DOUBLE,
  "numvotes" BIGINT,
  "ordering" BIGINT,
  "title" VARCHAR,
  "region" VARCHAR,
  "language" VARCHAR,
  "types" VARCHAR,
  "attributes" VARCHAR,
  "isoriginaltitle" BIGINT,
  "description" VARCHAR
);