Alternative data datasets
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Corporate and sovereign-level information supporting SFDR compliance regarding Principal Adverse Impact disclosures.
Structured line items from SEC 10-K and 10-Q filings between 2009 and 2023, plus company facts, fundamentals extracted straight from EDGAR.
Historical Data from SEC Company Filings
Smart meter data from London area
A joint release by Datamule, Teraflop AI, and Eventual provides the SEC-EDGAR dataset, comprising 590 GB of content drawn from all major filings in the SEC EDGAR database and totaling roughly 8 million samples and 43 billion tokens. The data was assembled using the datamule-python library and the official datamule API developed by John Friedman, with datamule serving as a Python package for collecting and manipulating such records.
10-K filings for S&P 500 companies retrieved from EDGAR, stored as Parquet with the filing text attached (MIT). A focused corpus for the large-cap annual disclosure cycle: risk factors, MD&A and segment detail for every S&P 500 name.
S&P 500 Corporate Filings (SEC EDGAR 10-K & 8-K Archive) Overview This dataset contains clean, structured public data exported directly from production runs of Apify actors. It serves as a benchmark and sample for lead qualification, market intelligence, research, and machine learning pipelines. Source Actor: captainhandsome/sec-edgar-filings-search Dataset Page: Public sample and schema Preconfig
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Datamule partnered with Teraflop AI and Eventual to publish the SEC-EDGAR dataset, which covers all major filings from the SEC EDGAR database and amounts to 590 GB across about 8 million samples and 43 billion tokens. Collection relied on the datamule-python library and John Friedman's official datamule API, tools designed in Python for gathering and handling SEC filing data.
Metadata for every EDGAR filing submitted to the U.S. Securities and Exchange Commission from 1994 through December 14, 2024, derived from the quarterly master index files and including CIKs, issuer names, and form types.
sec_filings is a small text dataset of 494 rows that pairs natural-language queries about U.S. securities filings with retrieved document facts and ground-truth answers. It is distributed under an unstated license on a public dataset hub.
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Machine-readable extraction of financial and operating figures drawn from publicly filed corporate documents.
Earnings-call transcripts for S&P 500 companies, tens of thousands of calls in English with timestamps, in Parquet (MIT). Direct input for call-tone and question-and-answer sentiment analysis across the large-cap earnings cycle.
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Free 2h sample: graduate trades, launches, launchpads, Meteora pools
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A cleaned, structured repository of job listings from multiple boards, with duplicate removal and records of when posts open and close.
Extract product catalogs, pricing, and vendor data from any Shopify store! Ou...
Scrape restaurant listings from Swiggy.com, India's #2 food delivery platfor...
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