Datasets

4,235 active FDIC-insured institutions with certificate number, location, bank class, primary regulator, Fed RSSD id, establishment date, office count, total assets, deposits, net income, ROA and ROE, from the FDIC BankFind API as of 2026-09-05.

1,000 most-starred public GitHub repositories with rank, full name, description, URL, stars, forks, open issues, primary language, SPDX licence, topics, creation, update and last-push timestamps, archived flag and repository size, from the GitHub REST search API as of 2026-09-06.

79,288 eBooks, audiobooks and other items in the Project Gutenberg collection with ebook number, media type, date added to the collection, title, language, authors with life dates, Library of Congress subject headings and classification codes, and Gutenberg bookshelves, from the official pg_catalog.csv feed as of 2026-09-06.

7,321 month-end rows of interest expense on the public debt (public issues and Government Account Series) across 47 expense group and security-type combinations: accrued interest, amortised discount and premium, savings bonds, TIPS inflation compensation and cash-basis GAS payments, each with the month's expense and the fiscal-year-to-date total in US dollars, from the Treasury's Fiscal Data "Interest Expense on the Public Debt Outstanding" table as of 2026-09-06.

250,910 CVE records published between 1 January 2020 and 2026-09-06 in the National Vulnerability Database: CVE id, publication and last-modified timestamps, NVD status, the CVSS v3.x base score, severity and vector string (232,487 scored; v3.1 preferred over v3.0 and NVD's own metric over a CNA's), CWE weakness ids, the English description capped at 1,000 characters and the number of references, one row per CVE. 10,662 rejected CVEs are kept with status Rejected and blank metrics. From the NVD CVE API 2.0 as of 2026-09-06.

Five years of sell-side analyst activity for the top 3,000 US-listed issuers, delivered as three complementary files: 85,777 individual upgrade/downgrade events, 73,147 individual price target changes, and 144,410 monthly aggregate strong-buy / buy / hold / sell / strong-sell counts. Each event row carries the analyst firm, previous and new grade or target, the stock price at the time of the call, and a link back to the originating news item. Read with pandas.readcsv(path, compression='gzip', parsedates=['publishedDate']). Useful for: analyst-momentum factors, upgrade/downgrade event studies, calibrating analyst accuracy by firm, building target-change feature stacks, and reconstructing consensus drift around earnings.

11,018 observations across 16 US housing series from FRED: starts, permits, completions, new and existing home sales, median price, Case-Shiller and FHFA indices, 30- and 15-year mortgage rates, homeownership and rental vacancy, months of supply, residential construction spending, rent CPI and mortgage delinquency. Long format with series name, frequency and unit on every row, full history to 2026-09-05.

21,171 close approaches of asteroids and comets within 0.05 au of Earth between 2000 and 2030, with object designation, orbit solution, approach date and time, nominal and minimum distance, relative and infinity velocities, time uncertainty and absolute magnitude, from the JPL Close-Approach Data API as of 2026-09-05.

Twenty years of daily open/high/low/close/volume bars for every current S&P 500 constituent (503 tickers including dual-class shares like BRK.A/BRK.B and GOOG/GOOGL). Date range: 2006-01-03 through 2026-09-05. Sourced live from Financial Modeling Prep and packaged as a single gzipped CSV — one row per (symbol, date), sorted by symbol then date ascending. Pandas, DuckDB, R, and most data tools read .csv.gz natively. Bedrock dataset for backtesting, factor research, event studies, and ML training. Note: prices reflect FMP's reported values at fetch time and are dividend/split adjusted as provided by FMP.

10,000 most-downloaded datasets on the Hugging Face Hub ranked by 30-day downloads, with repository id, author, downloads, likes, creation and last-modified timestamps, licence, task categories, size category, languages, gating flag and tag count, from the public Hub API as of 2026-09-06.

41,359 observations across 18 US credit and banking series from FRED: consumer and revolving credit, card and total loan delinquencies, C&I loans, bank credit and deposits, reserve balances, overnight reverse repo, the Treasury General Account, lending-standards survey, auto and card rates, the Chicago Fed NFCI, the St. Louis Fed stress index and Baa/Aaa spreads. Long format, full history to 2026-09-05.

Ten years of sell-side consensus quarterly estimates for 8,480 US-listed issuers, covering 175,834 quarter-periods. Each row carries low / avg / high consensus values across six fundamental lines — revenue, EBITDA, EBIT, net income, EPS, SG&A — plus analyst-coverage counts. Read with pandas.readcsv(path, compression='gzip', parsedates=['date']). Useful for: pairing with the Earnings Surprises listing for analyst-accuracy / drift research, tracking estimate revisions over time, building consensus-bias factors, training models on the dispersion (high − low) as a proxy for fundamental uncertainty.

18,980 quarter-end exchange rates (foreign currency units per US dollar) for 265 country-currency pairs, the official rates US government agencies must use to convert foreign-currency receipts and disbursements, from the Treasury's Fiscal Data "Treasury Reporting Rates of Exchange" table as of 2026-09-06. Includes many currencies absent from central-bank fixings.

972,762 daily rankings of the 1,000 most-viewed English Wikipedia articles from 2024-01-01 to 2026-09-04, with date, rank, article title and pageviews across desktop and mobile; Main_Page and Special: pages are excluded, rank is Wikimedia's own so a day keeps gaps where those were removed, and 1 days for which Wikimedia has published no list are absent; from the Wikimedia Pageviews API as of 2026-09-06.

15,000 most-downloaded PyPI packages with rank, project name, downloads over the 30 days to 2026-09-01 and the snapshot date, from the hugovk/top-pypi-packages monthly dump of the public PyPI download statistics as of 2026-09-06.

Five years of SEC Form 4 insider transaction filings for the top 918 US-listed companies by reporting history, covering 2021-01-04 through 2026-09-04. 601,965 transactions as a single gzipped CSV — one row per filed transaction. Columns include the filing date, transaction date, reporting insider name and role, transaction type (open-market buy/sell, option exercise, RSU vest, gift, etc.), shares transacted, price per share, total shares owned after the transaction, and a direct link to the EDGAR filing. Sourced from Financial Modeling Prep (Form 4 mirror of EDGAR). Read with pandas.readcsv(path, compression='gzip', parsedates=['filingDate', 'transactionDate']) or duckdb.read_csv('file.csv.gz'). Useful for: tracking insider sentiment, building cluster-buying signals, identifying executives unloading positions ahead of weakness, screen for management vs. board behavior divergence.

72,353 Federal Register documents published from 1 January 2024 to 2026-09-08: every rule, proposed rule, notice and presidential document with document number, publication date, issuing agencies, FR citation, the significance flag for rules, docket ids, links to the federalregister.gov HTML and GovInfo PDF versions and the abstract (capped at 1,000 characters), from the Federal Register API as of 2026-09-06.

7,386 observations of the Consumer Price Index for All Urban Consumers, all items, not seasonally adjusted (1982-84=100), for 11 metropolitan areas: New York, Chicago, Boston, Dallas-Fort Worth, Philadelphia, Detroit, Houston, Atlanta, Miami, San Francisco and Seattle, 1914-12-01 to 2026-07-01, from the BLS via FRED as of 2026-09-06. Long format with metro name and the area's current BLS publication frequency on every row: New York and Chicago monthly, Boston and Dallas bimonthly for odd months, the remaining areas bimonthly for even months (most areas were monthly before 1987 or 2018, so earlier history is denser).

21,565 entity-year observations of period life expectancy at birth in years for 236 countries and 29 regions, income groups and historical entities (world and continental aggregates carry OWID codes such as OWID_WRL; UN regional and income-group aggregates have no code), 1543 to 2023, from Our World in Data's life-expectancy grapher export as of 2026-09-06.

186,875 earthquakes of magnitude 4.5 and above worldwide from January 2000 to 2026-09-05, with time, epicentre, depth, magnitude and magnitude type, network, location text and review status, from the USGS FDSN event service. One row per event, ordered by time.

15,720 county-year rows for all 3,144 US counties and county equivalents, 2020 to 2024, with the July 1 population estimate and the components of change (births, deaths, natural change, international, domestic and net migration), keyed by five-digit county FIPS and year, from the Census Bureau's Vintage 2024 county totals file as of 2026-09-06.

21,586 entity-year observations of real GDP per capita in international dollars at 2011 prices (adjusted for inflation and for price differences between countries) for 165 countries and 13 regions and historical entities, from year 1 to 2022, as published in the Maddison Project Database 2023 and exported from Our World in Data's grapher as of 2026-09-06. The annotations column of the export is dropped; every row keeps entity, ISO code, year and value.

Every Senate and House Periodic Transaction Report (PTR) filed under the STOCK Act, as indexed by FMP. 10,100 Senate trades + 10,100 House trades = 20,200 transactions in 2 gzipped CSVs. Each row has the politician's name, party district, transaction date, disclosure date (often weeks/months later — that lag is itself a signal), transaction type (Purchase / Sale / Exchange), asset symbol, asset description, asset type (Stock, Option, Bond, Mutual Fund), amount range (STOCK Act bins like '$1,001 – $15,000'), spouse/dependent owner flag, comment, and a direct URL to the official PDF/HTML disclosure. Read with pandas.readcsv(path, compression='gzip', parsedates=['transactionDate', 'disclosureDate']). Polymarket-trader catnip — track Pelosi, Crapo, Tuberville, et al. in near-real-time. Useful for: lawmaker-replication strategies, sector-rotation signals from committee members trading regulated industries, and detecting unusual transaction clusters around legislation.

3,809 country-year observations from the Excessive Deficit Procedure tables for 31 geographies (EU and euro-area aggregates plus every EU member state): general government consolidated gross debt and net lending/net borrowing, each as a percentage of GDP and in million euro, 1995 to 2025, from the Eurostat dissemination API as of 2026-09-06. Long format with na_item and unit on every row.