Dataset
sec-edgar-rpt
sec-edgar-rpt is a Hugging Face dataset published by codewithdark that aggregates SEC EDGAR filings, packaged as a single text column with a train split of roughly 3.9 million rows. It is distributed under an unstated license and is catalogued for text and machine-learning workflows.
Data preview
Dataset card
What this dataset contains
The dataset holds parsed SEC EDGAR filing content drawn from the public EDGAR system, consolidated into a text format suitable for downstream natural-language processing. According to the metadata, it carries between one and ten million records and exposes a single string field rather than tabular financials. The release ships with one split labelled train, containing 3,894,052 rows.
Structure and fields
Schema information lists one column named text of dtype string, indicating each row stores raw filing text rather than pre-extracted financial line items. Sample rows include boilerplate headers such as privacy-enhanced message markers and MIME-style proc-type lines, suggesting the corpus preserves original document structure. No further columns such as ticker, form type, filing date, or CIK are exposed in the provided schema.
How analysts use it
Because the data is text-centric, it lends itself to NLP tasks like named-entity recognition, topic modelling, and building retrieval systems over regulatory filings rather than direct quantitative screening. Investment workflows would need to enrich the text column with metadata such as form type, issuer, and filing date before it could feed fundamentals-based strategies. Given the unstated license and missing issuer-level identifiers, downstream use should confirm redistribution rights and supplementary fields before integration into a production pipeline.
Documentation & references 1
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SEC EDGAR 10-K & 10-Q financial statements for 2,600+ NASDAQ companies.
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