75k Goodreads Book Dataset
Budget: $30 – $250 USD
I need a clean, well-structured database containing at least 75,000 unique book records pulled from Goodreads. Fiction and non-fiction titles are both in scope, and I am happy to include works from any publication year.
For every book, please capture all of the following fields:
• Title
• Author
• Average rating and total number of ratings (both numbers, not either/or)
• Year of first publication
• Full description / synopsis text
• Primary genre(s) as labelled on Goodreads
• ASIN
• ISBN-10 and ISBN-13 (where available)
• Direct image URL for the book cover
The final deliverable should be delivered in a structured format that loads easily into a relational database or data-science workflow (CSV, TSV, or SQL dump are all fine). Each record must be unique, with duplicates removed and fields consistently formatted.
I will consider the project complete when:
1. The file contains ≥ 75,000 rows.
2. All listed fields are present for every row (use “N/A” only when Goodreads truly lacks the value).
3. Spot checks confirm data accuracy against live Goodreads pages.
Feel free to use the official Goodreads API, ethical scraping, or a hybrid approach—whatever produces the most complete and reliable dataset. Let me know your proposed method, timeline, and any questions so we can move forward quickly.
For every book, please capture all of the following fields:
• Title
• Author
• Average rating and total number of ratings (both numbers, not either/or)
• Year of first publication
• Full description / synopsis text
• Primary genre(s) as labelled on Goodreads
• ASIN
• ISBN-10 and ISBN-13 (where available)
• Direct image URL for the book cover
The final deliverable should be delivered in a structured format that loads easily into a relational database or data-science workflow (CSV, TSV, or SQL dump are all fine). Each record must be unique, with duplicates removed and fields consistently formatted.
I will consider the project complete when:
1. The file contains ≥ 75,000 rows.
2. All listed fields are present for every row (use “N/A” only when Goodreads truly lacks the value).
3. Spot checks confirm data accuracy against live Goodreads pages.
Feel free to use the official Goodreads API, ethical scraping, or a hybrid approach—whatever produces the most complete and reliable dataset. Let me know your proposed method, timeline, and any questions so we can move forward quickly.