https://www.kaggle.com/datasets/danielgrijalvas/movies

About Dataset
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.