This repository contains the dataset used for training an ML model to predict the box office success (revenue) from other parameters, such as Genre, Budget, Popularity, Star Power, etc.
The data was taken from various TMDB datasets found on Kaggle, and then further run through the TMDB and OMDB APIs to fetch data for all features. Some the movies were also extracted from the TMDB Dataset through it's APIs directly.
The dataset has 6065 movies in total, with the following features:
- Genres
- ID
- Original Language
- Original Title
- Overview
- Popularity Rating
- Release Date
- Title
- TMDB Rating
- TMDB Vote Count
- IMDb ID
- Budget
- Revenue
- Production Companies
- Cast
- Crew
- Production Countries
- Spoken Languages
- Runtime
- Tagline
- MPAA Rating
- IMDb Rating
- IMDb Vote Count
- Star Power
The popularity index of the most popular actor in the movie was taken to be the Star Power. The IMDb Ratings and Vote Count was taken from the OMDB API, along with the MPAA rating.