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README.md
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# Dataset Card for "BrightData/Goodreads-Books"
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## Dataset Summary
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Explore a collection of millions of books with the Goodreads dataset, comprising over 6.3M structured records and 14 data fields.
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Each entry includes all major data points such as including URLs, book IDs, titles, authors, star ratings, number of ratings, reviews, summaries, genres, publication dates, author details, community reviews and prices.
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## Data Dictionary
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- Parsing: Extracted raw data was parsed to convert it into a structured format.
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- Cleaning: The cleaning process involved removing any irrelevant or erroneous entries to enhance data quality.
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### Validation
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To ensure data integrity, a validation process was implemented. Each entry is checked across various attributes, including:
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This ensures that the dataset meets the high standards of quality necessary for analysis, research and modeling.
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To explore additional free and premium datasets, visit our website [brightdata.com](https://www.brightdata.com)
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## Example JSON
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<div style="max-height: 300px; overflow-y: auto; border: 1px solid #ccc; padding: 10px;">
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# Dataset Card for "BrightData/Goodreads-Books"
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If you are using this dataset, we would love your feedback: [Link to form](https://docs.google.com/forms/d/e/1FAIpQLSdhxzlCEA8SGjjWZp-U6539oYmzdxlQ_Qb0pTPV6PqvmyrygA/viewform?usp=sf_link)
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## Dataset Summary
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Explore a collection of millions of books with the Goodreads dataset, comprising over 6.3M structured records and 14 data fields.
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Each entry includes all major data points such as including URLs, book IDs, titles, authors, star ratings, number of ratings, reviews, summaries, genres, publication dates, author details, community reviews and prices.
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For a complete list of data points, please refer to the full "Data Dictionary" provided below.
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To explore additional free and premium datasets, visit our website [brightdata.com](https://www.brightdata.com)
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## Data Dictionary
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- Parsing: Extracted raw data was parsed to convert it into a structured format.
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- Cleaning: The cleaning process involved removing any irrelevant or erroneous entries to enhance data quality.
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### Validation
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To ensure data integrity, a validation process was implemented. Each entry is checked across various attributes, including:
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This ensures that the dataset meets the high standards of quality necessary for analysis, research and modeling.
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## Example JSON
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<div style="max-height: 300px; overflow-y: auto; border: 1px solid #ccc; padding: 10px;">
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