GoodReads Best Books by Kaggle | Media and Entertainment

About this Dataset

GoodReads Best Books

Ratings, Genres, Awards, and More

About this dataset

This dataset provides a comprehensive collection of 52478 books that have been listed in GoodReads' Best Books Ever, letting curious readers and irreplaceable researchers explore the depths of these renowned titles. The dataset features diverse information on each book, from ratings to awards to the characters that make up each narrative, with plenty of details about all aspects for an unparalleled understanding. Discover page numbers and editions, genres and languages, first publish dates and prices--all available in one impeccable dataset! Evaluate promotions and celebrate successes with ratings by stars or viewer liked percentages. Dive into descriptions for an intensified look into plot lines or unearthly settings featured in the texts. With colorful cover images plus records of awards won by these beloved classics, this is sure to be a meticulous treasure trove perfect for any avid reader or researcher with an appetite for literary investigation

More Datasets

For more datasets, click here.

Featured Notebooks

🚨 Your notebook can be here! 🚨!

How to use the dataset

Understand the variables in the dataset: Before attempting to work on the data set it’s important that you understand what each variable means and how it might be used in analysis or comparison between books or authors. This includes variables such as rating, awards received and genre etc., which are all listed at the beginning of this guide

Explore data across different categories: This dataset can help you explore data if you want to get an understanding of what type of books are most successful based on rating or awards received for example. You can also filter by categories such as genre so that your results give you a narrowed insight into one particular type of book/author etc..

Compare different authors: You can take a look at different authors who appear in this database and compare them based off their ratings and other factors like number of pages, popularity amongst readers (the likedPercent) etc so that you can get an understanding if certain super popular authors are enjoying more success than others with their releases over time

Analyse books across different settings: Furthermore there is also an interesting way in which one could analyse various settings; setting describes ‘where and when’ a book is set – think City vs Country life - so these two types could be compared using our database; similarly – comparing authors who write mostly sci-fi novels vs historical biographies could give us insights into reader preferences

5.: Utilise coverImg link: Finally there is also another unique aspect to our data – something we call coverImg–which allows us visualise what cover images look like when examining a particular book thus allowing for even more interesting exploration into topics like art direction within publishing!

These pointers should have given everyone interested in exploring this rich source material with some ideas on how they could use it towards furthering research objectives in good reads best books ever lists

Research Ideas

To create an author leaflet featuring authors with books on the GoodReads Best Books Ever list, highlighting their awards and ratings to help potential readers better understand them.

To compile a list of book series that have been recognized by Goodreads as essential reading for certain genres or groupings of topics, such as crime novels and romance books.

To compare book series over different publications, editions, ratings and likability among readers with different languages in order to study how successful books are received by different audiences across the globe

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: books_1.Best_Books_Ever.csv

Column name	Description
title	The title of the book. (String)
series	The series the book belongs to, if any. (String)
author	The author of the book. (String)
rating	The average rating of the book on GoodReads. (Float)
description	A brief description of the book. (String)
language	The language the book is written in. (String)
isbn	The ISBN number of the book. (String)
genres	The genres the book falls into. (String)
characters	The characters featured in the book. (String)
bookFormat	The format of the book (e.g paperback or e-book). (String)
edition	The edition of the book. (String)
pages	The number of pages in the book. (Integer)
publisher	The publisher of the book. (String)
publishDate	The date the book was published. (Date)
firstPublishDate	The date the book was first published. (Date)
awards	Any awards the book has received. (String)
numRatings	The number of ratings the book has received. (Integer)
ratingsByStars	The ratings the book has received broken down by star ratings. (String)
likedPercent	The percentage of readers who liked the book. (Float)
setting	The setting of the book. (String)
coverImg	The cover image of the book. (String)
bbeScore	The score of the book on GoodReads' Best Books Ever list. (Float)
bbeVotes	The number of votes cast for the book on GoodReads' Best Books Ever list. (Integer)
price	The price of the book. (Float)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Books 1 Best Books Ever

@kaggle.thedevastator_comprehensive_overview_of_52478_goodreads_best_b.books_1_best_books_ever

40.24 MB
52478 rows
25 columns


CREATE TABLE books_1_best_books_ever (
  "bookid" VARCHAR,
  "title" VARCHAR,
  "series" VARCHAR,
  "author" VARCHAR,
  "rating" DOUBLE,
  "description" VARCHAR,
  "language" VARCHAR,
  "isbn" VARCHAR,
  "genres" VARCHAR,
  "characters" VARCHAR,
  "bookformat" VARCHAR,
  "edition" VARCHAR,
  "pages" VARCHAR,
  "publisher" VARCHAR,
  "publishdate" VARCHAR,
  "firstpublishdate" VARCHAR,
  "awards" VARCHAR,
  "numratings" BIGINT,
  "ratingsbystars" VARCHAR,
  "likedpercent" DOUBLE,
  "setting" VARCHAR,
  "coverimg" VARCHAR,
  "bbescore" BIGINT,
  "bbevotes" BIGINT,
  "price" VARCHAR
);