Name: Best Books (10k) Multi-Genre Data
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Best Books (10k) Multi-Genre Data

Context

This data was collected in a personal attempt to identify more books that one would like, based on ones they may have read in the past. It comprises 10k of the most recommended books of all time.

This data was collected in an attempt to aid my Movies/Shows dataset to help with projects concerning cross-content analysis/recommendations for instance.

Please Upvote if this helps you!

Content

Book - Name of the book. Soemtimes this includes the details of the Series it belongs to inside a parenthesis. This information can be further extracted to analyse only series.
Author - Name of the book's Author
Description - The book's description as mentioned on Goodreads
Genres - Multiple Genres as classified on Goodreads. Could be useful for Multi-label classification or Content based recommendation and Clustering.
Average Rating - The average rating (Out of 5) given on Goodreads
Number of Ratings - The Number of users that have Ratings. (Not to be confused with reviews)
URL - The Goodreads URL for the book's details' page

Inspiration

Cluster books/authors based on Description and Genre
Content based recomendation system using Genre, Description and Ratings
Genre prediction from Description data (Multi-label classification)
Can be used in conjunction with my IMDb dataset with descriptions for certain use cases

Acknowledgements

The data was collected from Goodreads from the list - Books That Everyone Should Read At Least Once

Tables

Goodreads Data

@kaggle.ishikajohari_best_books_10k_multi_genre_data.goodreads_data

7.47 MB
10,000 rows
8 columns

CREATE TABLE goodreads_data (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "book" VARCHAR,
  "author" VARCHAR,
  "description" VARCHAR,
  "genres" VARCHAR,
  "avg_rating" DOUBLE,
  "num_ratings" BIGINT,
  "url" VARCHAR
);