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Top Film Reviews and Ratings Data
Product Reviews & Feedback
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About
Movie reviews sourced from the ReelView website, featuring some of the most popular and well-known films of all time. This collection is ideal for practising data analysis, visualisation, and data preprocessing techniques. It serves as an excellent resource for beginners in data science and analysis looking to develop and refine their skills. The data may contain some 'nan' values, which can be managed easily.
Columns
- title: The title of the movie.
- stars_rating: The star rating given to the movie, on a scale out of 5.
- run_time: The duration of the movie in minutes.
- release_date: The year the movie was released.
- mpaa_rating: The demographic rating for the movie, such as indicating violence or profanity.
- genre: The genre or genres associated with the movie (e.g., DRAMA, COMEDY).
- director: The name of the movie's director.
- cast: The actors who starred in the movie.
Distribution
- Format: The data is provided in a single CSV file named
ReelView.csv. - Size: The file size is approximately 756.42 kB.
- Structure: The dataset is structured into 8 columns and contains 3,990 records. Some columns contain missing values.
Usage
This dataset is well-suited for a variety of applications, including:
- Practising data analysis and data preprocessing skills.
- Developing and testing graphing and data visualisation techniques.
- Performing exploratory data analysis on movie trends.
- Building recommendation engine prototypes.
Coverage
The dataset offers global coverage, containing reviews for a wide array of well-known movies. The temporal scope for movie releases spans from 1970 to 2023. There are no specific demographic limitations mentioned, making it broadly applicable. Note that data availability varies, with some records missing information for columns like
release_date, mpaa_rating, and run_time.License
CC0: Public Domain
Who Can Use It
- Data Science Beginners: Can use this dataset to practice fundamental skills in data cleaning, analysis, and visualisation.
- Students: Ideal for academic projects related to film studies, data analytics, or computer science.
- Data Analysts: Can perform exploratory analysis to uncover trends in movie ratings, genres, and run times over the years.
- Hobbyists: Film enthusiasts can use this data to explore patterns and insights about their favourite movies and directors.
Dataset Name Suggestions
- ReelView Movie Review Analytics
- Top Film Reviews and Ratings Data
- Global Movie Ratings Dataset (1970-2023)
- ReelView Film Analysis Collection
Attributes
Original Data Source:Top Film Reviews and Ratings Data
QUALITY