The TMDb Dataset contains information about 10000 plus movies collected from "The Movie Database". This is a csv dataset that contains 21 columns and 10866 rows
This TMDb dataset contains the following columns:
- id - A unique identifier for each movie.
- imdb_id - A unique identifier for each movie on the TMDb dataset.
- popularity - A numeric representation of the movie popularity.
- budget - The budget in which the movie was made.
- revenue - The revenue generated per movie.
- original_title - The title of the movie before released.
- cast - The name of lead and supporting actors.
- homepage - A link to the homepage of the movie.
- director - the director(s) of the movie
- tagline - Each movies tagline.
- keywords - The keywords or tags associated to the movie.
- overview - A brief description of the movie.
- runtime - The runtime of the movie in minutes.
- genres - The genre of the movie, Adventure, Drama, etc.
- production_companies - The production house of the movie.
- release_date - The date on which it was released.
- vote_count - The number of votes per movie
- vote_average - average ratings the movie recieved.
- released_year - The year each movies was released
- budget_adj - shows the full budget per movie in dollars.
- revenue_adj - shows the full revenue per movie in dollars.
- Are high budget movies more popular?
- Which company produced the highest movies?
From my analysis: Q1: There's a weak positive correlation between movies budget and popularity. This means most times the budget of a movie does not influence its popularity.
Q2: The companies from the known list of producers that produced the most movies is "Universal Pictures"
During my analysis of the production companies, I discovered that majority of the production companies data was not entered, hence did not really give an accurate results of the company that produced the most movies.