Two joinable datasets on the best-selling books of all time: 285 title rows (174 individual books and 111 series, unified with a Type column; the regularly-updated dictionaries and annuals excluded) with the sales claim as written beside a numeric copies-in-millions twin, original language, genre, first-published year and installment counts, and 264 author rows on the movie-stars formula: birth and death dates, age at death, split birthplace, marriage and children counts, plus columns derived across the files, titles listed, total claimed copies, and age at first bestseller (NA for posthumous publications; co-authored series date from the series' first year).
549 rows across 2 joinable files, with 25 columns in total: Title, Type, Author, Original_Language, Genre, First_Published, Installments, Approximate_Sales, Copies_Millions, Title_URL, Author, Birth_Date, Death_Date, Age_at_Death, Birth_City, Birth_State, Birth_Country, Number_of_Marriages, Avg_Marriage_Length_Years, Number_of_Children, Books_Listed, Copies_Millions_Total, First_Bestseller_Year, Age_at_First_Bestseller, Author_URL.
It is built by programmatically scraping en.wikipedia.org, last pulled on 2026-09-02. Datasets are versioned; older versions stay downloadable.
Yes. Every CodeSights dataset is completely free as a CSV download; a free account is all it takes. Anyone can preview the data without signing in.
Yes. The exact Python scraper that built it is viewable on the dataset page by any signed-in member, so every number is reproducible.
Join the files on author name. Multi-author titles list every name comma-joined, so match on the Author file's exact name within the books' Author field.
Automated scraping leaves room for error and the underlying sources change over time, so no version is guaranteed accurate or complete. If a number matters, verify it against the original source.