bstarrs/goodreads-books

--- 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: - 📚 Book recommendation systems - 📊 Literary data analysis - 🤖 Machine learning projects - 📈 Rating prediction models - 🔍 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 ```python 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.--- 许可协议：CC0-1.0 任务类别： - 文本分类 - 文本生成 语言： - 英语 标签： - 书籍 - Goodreads - 网络爬取 - 推荐系统 - 文学 数据规模： - 1000 < 样本数 < 10000 --- # Goodreads书籍数据集（Goodreads Books Dataset） ## 数据集说明 本数据集为从Goodreads平台爬取的综合性书籍数据集，涵盖评分、作者、书名及各类书籍特征。 本数据集共包含3045本图书，每本图书对应20项特征，均通过Goodreads平台爬取获取。该数据集适用于以下场景： - 📚 图书推荐系统 - 📊 文学数据分析 - 🤖 机器学习项目 - 📈 评分预测模型 - 🔍 图书发现算法 ## 数据集结构 ### 特征项 | 列名 | 数据类型 | 特征描述 | |--------|------|-------------| | rank | int64 | 图书排名 | | percentile_rank | float64 | 图书百分位排名 | | book_id | int64 | 图书唯一标识符 | | title | object | 图书书名 | | author | object | 图书作者 | | rating | float64 | 图书评分 | | rating_category | object | 图书评分类别 | | rating_tier | object | 图书评分层级 | | is_high_rated | bool | 是否为高评分图书 | | title_length | int64 | 书名字符长度 | | title_complexity | object | 书名复杂度 | | word_count | int64 | 图书单词总数 | | author_count | int64 | 作者数量 | | author_name_length | int64 | 作者姓名字符长度 | | has_series_info | bool | 是否包含系列丛书信息 | | series_number | float64 | 丛书序列编号 | | title_type | object | 书名类型 | | has_subtitle | bool | 是否包含副标题 | | has_middle_name | bool | 作者是否包含中间名 | | estimated_popularity | object | 图书预估热度 | ### 统计信息 - **总记录数**：3045条 - **文件大小**：0.43 MB - **数据完整度**：97.0% - **平均评分**：4.06 - **评分区间**：0.00 - 4.93 ## 使用方法 python from datasets import load_dataset # 加载数据集 dataset = load_dataset("codealchemist01/goodreads-books") # 访问数据 df = dataset['train'].to_pandas() print(df.head()) ## 数据采集 本数据集通过合规的网络爬取方式从Goodreads.com采集所得，具体遵循以下伦理爬取规范： - 采用合理的请求速率限制 - 遵守robots.txt协议 - 未采集任何个人用户数据 ## 引用声明 若您在研究中使用本数据集，请按照以下格式引用： @dataset{goodreads_books_2025, title={Goodreads Books Dataset}, author={Kutay Ahin}, year={2025}, url={https://huggingface.co/datasets/codealchemist01/goodreads-books} } ## 许可协议 本数据集采用CC0 1.0通用许可协议发布。