Data Sources
FRED, SEC EDGAR, BLS, exchange feeds: how to pull them, parse them, and not misread them.
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The CPI basket explained, from the BLS relative importance tables
Shelter is 35.6% of the CPI-U basket for 2026 and energy 6.4%, yet energy supplied 38% of the index's rise from December to August. The weights, and how to use them.
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Data revisions in FRED: ALFRED vintages and why final is not final
Every payroll and real GDP vintage since 2010, pulled from ALFRED without a key: how far first prints moved, the annual benchmarks, and the level trap.
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Reading SEC EDGAR in Python: submissions, full-text search, XBRL facts
The three free EDGAR JSON endpoints in one standard-library script: a company's filings by accession number, full-text search hits, and deduplicated XBRL facts.
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Where free market data actually comes from, and what each source lags
Eight FRED series traced to the agency or exchange that produces them, with native frequency and the days between last observation and retrieval date, computed.
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Pulling FRED series without an API key, cleanly, in Python
FRED serves every series as a plain CSV with no key. A standard-library script that downloads, merges, and coverage-checks any list of series ids, with the gotchas.
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BLS data in Python: CPI components and payrolls without a key
The BLS public API v1 needs no key. A script pulls CPI components and the jobs headline, handles the "-" returned for a missing month, and prints 12-month changes.