One row per famous dead business and what killed it: 228 hand-curated companies across retail, technology, finance, airlines, autos, software, video games, restaurants, media and industry, from Baldwin Locomotive (folded in 1951) to Skype (shut down 2025). There is no Wikipedia list for this; the spine is curated in the scraper and EVERY row is fact-checked against the company's own article before it ships: the article must read as dead, must support the killer keywords, and the curated death year is cross-checked against the article's Defunct year. Killed_By names the finisher, from Netflix (which killed Blockbuster at age 13, conceding a 12-year head start, both shipped as numeric columns) to Amazon, Walmart, the 2008 crisis and the parent companies that shot their own divisions; Killer_Type separates company-on-company disruption from technology shifts, crises, scandals, self-inflicted wounds and the pandemic. Death_Event (bankruptcy, liquidation, acquisition, merger, shutdown, nationalization, breakup) and Brand_Today (gone, zombie brand, revived, shrunken survivor, absorbed) record the honest shades of corporate death, so Kodak and Sears sit beside Circuit City without an argument. Revenue with its currency and year, employees and locations carry peak-era values from the infobox or the article's own prose, with era guards against successor-company figures; Lehman Brothers died at 158. The last CEO rides along with birth date and birthplace wherever their own article verifies the link. Built for studying disruption, with a 15-test known-facts suite.
228 rows in one CSV file, with 29 columns in total: Company, Product, Category, Founded_Year, Death_Year, Age_at_Death, Death_Event, Brand_Today, Killed_By, Killer_Type, Killer_Founded_Year, Killer_Age_at_Kill, Years_Head_Start, Revenue_Millions, Revenue_Currency, Revenue_Year, Employees, Employees_Year, Locations, Locations_Year, Headquarters, HQ_Country, Last_CEO, CEO_Birth_Date, CEO_Birth_Place, CEO_Birth_Country, Company_URL, Killer_URL, CEO_URL.
It is built by programmatically scraping en.wikipedia.org, last pulled on 2026-09-10. 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.
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.