metadata
license: cc0-1.0
task_categories:
- text-classification
- text-generation
language:
- en
tags:
- books
- goodreads
- web-scraping
- recommendation-systems
- literature
size_categories:
- 1K<n<10K
Goodreads Books Dataset
Dataset Description
A comprehensive dataset of books scraped from Goodreads, including ratings, authors, titles, and various book characteristics.
This dataset contains 3045 books with 20 features each, scraped from Goodreads. It's perfect for:
- ๐ Book recommendation systems
- ๐ Literary data analysis
- ๐ค Machine learning projects
- ๐ Rating prediction models
- ๐ Book discovery algorithms
Dataset Structure
Features
| Column | Type | Description |
|---|---|---|
| rank | int64 | Book rank |
| percentile_rank | float64 | Book percentile rank |
| book_id | int64 | Book book id |
| title | object | Book title |
| author | object | Book author |
| rating | float64 | Book rating |
| rating_category | object | Book rating category |
| rating_tier | object | Book rating tier |
| is_high_rated | bool | Book is high rated |
| title_length | int64 | Book title length |
| title_complexity | object | Book title complexity |
| word_count | int64 | Book word count |
| author_count | int64 | Book author count |
| author_name_length | int64 | Book author name length |
| has_series_info | bool | Book has series info |
| series_number | float64 | Book series number |
| title_type | object | Book title type |
| has_subtitle | bool | Book has subtitle |
| has_middle_name | bool | Book has middle name |
| estimated_popularity | object | Book estimated popularity |
Statistics
- Total Records: 3,045
- File Size: 0.43 MB
- Data Quality: 97.0% complete
- Average Rating: 4.06
- Rating Range: 0.00 - 4.93
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("codealchemist01/goodreads-books")
# Access the data
df = dataset['train'].to_pandas()
print(df.head())
Data Collection
The data was collected through web scraping of Goodreads.com using ethical scraping practices:
- Respectful rate limiting
- Robots.txt compliance
- No personal user data collected
Citation
If you use this dataset in your research, please cite:
@dataset{goodreads_books_2025,
title={Goodreads Books Dataset},
author={Kutay Ahin},
year={2025},
url={https://huggingface.co/datasets/codealchemist01/goodreads-books}
}
License
This dataset is released under the CC0 1.0 Universal License.