Dark Mode
Cinematic History and Ratings Collection
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Serves as a robust foundation for multiple analytical projects by tracking and detailing cinematic releases and user engagement over decades. It is an essential resource for analysing film history, identifying box office trends, and exploring audience reception through user ratings. The data is highly valuable for Natural Language Processing (NLP) tasks, allowing users to apply tools to the provided plot summaries for sentiment analysis or text classification, discovering insights from movie history.
Columns
- id: A unique identifier assigned to the movie.
- title: The movie's commonly known name or title.
- original_title: The movie’s original title as initially released in its native language.
- overview: A brief summary or synopsis of the movie’s plot, particularly useful for textual analysis applications.
- release_date: The official release date of the movie, provided in the YYYY-MM-DD format.
- vote_average: The average user rating for the film, scaled between 0 and 10, as sourced from TMDb.
Distribution
The data is delivered in CSV format (
Trending_Movies.csv) and has a file size of 3.58 MB. It consists of 10,000 total records and includes 10 distinct columns detailing various film attributes and metrics. The expected update frequency for this dataset is quarterly.Usage
Ideal applications include discovering insights through data visualization tools such as Matplotlib or Seaborn. Users can employ NLP libraries like spaCy and NLTK to process the 'overview' data for tasks like sentiment analysis and text classification. The dataset is suitable for training machine learning models to predict audience success or for undertaking detailed historical trend modelling in the entertainment sector.
Coverage
The dataset focuses on global cinematic releases. The time range covered by the official release dates spans over a century, beginning on 1st January 1900 and extending up to 17th December 2031, providing a deep historical view alongside projected future dates.
License
CC0: Public Domain
Who Can Use It
- Data Science Enthusiasts: To practise data cleaning, analysis, and visualization techniques.
- Machine Learning Practitioners: For developing and training models for content recommendation or box office prediction.
- Developers: Those building applications that require movie metadata or trending historical data.
- Movie Buffs/Researchers: Interested in studying long-term trends and user engagement across decades of film history.
Dataset Name Suggestions
- Global Movie Trends Data
- Cinematic History and Ratings Collection
- Decades of Film Metrics
- Trending Movies (1900–2031)
Attributes
Original Data Source: Cinematic History and Ratings Collection
QUALITYLoading...