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Global Movie Financials and Ratings
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About
Details on over 5000 movies sourced from IMDb are available, featuring key attributes such as ratings, cast, director, and financial data. This collection is ideal for exploring cinematic trends, building recommendation systems, and performing predictive analysis on movie success factors.
Columns
- Title: The name of the movie.
- Average Rating: The average user rating from IMDb.
- Director: The name of the movie's director or directors.
- Writer: The writer or writers credited for the movie.
- Metascore: A critic score sourced from Metacritic; note that some data may be missing.
- Cast: The main actors featured in the movie.
- Release Date: The date the movie was released.
- Country of Origin: The country or countries where the movie was produced.
- Languages: The languages spoken in the movie.
- Budget: The production budget for the movie; this column contains some non-numeric values.
- Worldwide Gross: The total worldwide box office earnings; this column has some missing data.
- Runtime: The duration of the movie in minutes.
Distribution
The data is provided in a single CSV file named
IMDB_Movies_Dataset.csv with a size of 2.23 MB. It contains information for over 5000 movies structured across 13 columns.Usage
- Exploratory Data Analysis (EDA): Analyse trends in movie ratings, budgets, and revenues.
- Recommendation Systems: Develop models to recommend movies based on genre, director, cast, or ratings.
- Predictive Modelling: Create models to estimate a movie's potential revenue or rating based on its features.
Coverage
The dataset's geographic coverage is global, with the 'Country of Origin' column detailing production countries. It includes films with release dates spanning various years. There are no specific demographic limitations mentioned. Note that financial data like 'Budget' and 'Worldwide Gross', along with 'Metascore', have a significant number of missing values.
License
CC0: Public Domain
Who Can Use It
- Data Scientists: For building and training machine learning models, such as predictive engines for box office success.
- Data Analysts: For conducting exploratory data analysis to uncover insights and trends within the film industry.
- Students and Researchers: For academic projects related to film studies, market trends, and data analysis.
- App Developers: For creating applications that provide movie recommendations or display movie analytics.
Dataset Name Suggestions
- IMDb 5000+ Movie Analytics Dataset
- Global Movie Financials and Ratings
- Movie Industry Performance Metrics
- IMDb Film Data for Predictive Modelling
Attributes
Original Data Source: Global Movie Financials and Ratings
QUALITY