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Best Books Ever Data
Data Science and Analytics
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Free
About
Explore a rich collection of 50,000 book titles originally scraped from Goodreads, specifically from their "Best Books Ever" list. This dataset offers in-depth details on each book, going beyond the limitations of the official Goodreads API, and is ideal for understanding literary trends, reader preferences, and book popularity. It provides valuable insights into diverse aspects of published works, including ratings, reviews, and detailed metadata.
Columns
- id: A unique identifier for each book.
- title: The primary title of the book.
- link: A direct link to the book's listing on Goodreads.
- series: Indicates if the book is part of a series.
- cover_link: A URL to the book's cover image.
- author: The name of the book's author.
- author_link: A link to the author's profile page on Goodreads.
- rating_count: The total number of ratings the book has received.
- review_count: The total number of written reviews for the book.
- average_rating: The average rating awarded to the book, typically on a scale of 1 to 5.
- five_star_ratings: The count of ratings that were five stars.
- four_star_ratings: The count of ratings that were four stars.
- three_star_ratings: The count of ratings that were three stars.
- two_star_ratings: The count of ratings that were two stars.
- one_star_ratings: The count of ratings that were one star.
- number_of_pages: The total number of pages in the book.
- date_published: The original publication date of the book.
- publisher: The company responsible for publishing the book.
- original_title: The original title of the book, if different from the primary title.
- genre_and_votes: A list of genres associated with the book, along with the number of users who voted for each genre.
- isbn: The International Standard Book Number.
- isbn13: The 13-digit International Standard Book Number.
- asin: The Amazon Standard Identification Number.
- settings: The locations where the story takes place.
- characters: The main characters featured in the book.
- awards: Any awards or nominations the book has received.
- amazon_redirect_link: A Goodreads link that redirects to the book's listing on Amazon.
- worldcat_redirect_link: A Goodreads link that redirects to the book's listing on WorldCat.
- recommended_books: A list of IDs for similar books recommended by Goodreads.
- books_in_series: A list of IDs for other books belonging to the same series.
- description: A textual summary or description of the book's content.
Distribution
The dataset is provided in a CSV file format, named
goodreads_books.csv, with a file size of approximately 104.16 MB. It contains data for 50,000 unique book titles, with approximately 52.2k records, and features 31 distinct attributes (columns) for each entry.Usage
This dataset is well-suited for a variety of applications, including:
- Developing and training book recommendation engines.
- Conducting literary market analysis and trend identification.
- Performing sentiment analysis on book reviews.
- Academic research into publishing patterns and reader behaviour.
- Building data-driven applications for book enthusiasts and literary communities.
Coverage
The data primarily covers books listed on Goodreads' "Best Books Ever" list. While geographical and demographic information is not directly specified for the dataset's scope, the platform itself is global. The publication dates of the books vary significantly, with "2009" noted as a common publication year, reflecting a snapshot of popular and critically acclaimed literature up to the point of scraping.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Machine Learning Engineers: For building and evaluating recommendation systems, clustering books by genre or popularity, and natural language processing on descriptions and reviews.
- Literary Scholars and Researchers: To analyse trends in literature, study author popularity, and examine the correlation between ratings, reviews, and book characteristics.
- Market Researchers and Publishers: To identify popular genres, understand consumer preferences, and inform publishing strategies.
- Application Developers: For integrating book data into websites, mobile applications, or digital library projects.
Dataset Name Suggestions
- Goodreads Book Catalogue
- Best Books Ever Data
- Literary Ratings and Reviews
- Global Book Insights
- Digital Bookshelf Analytics
Attributes
Original Data Source: Best Books Ever Data
QUALITY