For Data Scientists & ML Engineers · Home Improvement Retail
Home Improvement Retail Data for Data Scientists & ML Engineers
Home Improvement Retail data for data scientists: 3 datasets on one shelf. Every one delivered as API, files, or warehouse rows.
financial time series api for backtesting · alternative data for quantitative research · where to get training data for home improvement retail models
API, files, or your warehouse. Daily, weekly, or hourly.
What home improvement retail data qualifies for data-science work?
Home Improvement Retail is one of the industries Datadory catalogs without a primary-tagged record: the viability roll-up assigns it 0 primary and 13 secondary datasets, all pooled from adjacent sectors. Cadence runs monthly, monthly and quarterly — none of the 22.6% daily-refresh behavior you find catalog-wide. The wider 13-record industry pool sits on the home-improvement-retail data hub.
How do you nowcast DIY demand with the Census MARTS API?
The catalog response is DCAT JSON-LD conforming to Project Open Data v1.1, typed as both a time series and a data cube at United States geography. Coverage is national only, one observation per kind of business per month per adjustment flag, across roughly 40-50 retail categories per release. For nowcasting, MARTS's value is timing: advance estimates land about two weeks after each reference month closes, so features built from it precede revised MRTS values. Licensing is commercial delivery terms 1.0 — reuse without restriction.
Which MRTS series support inventory and working-capital models?
MRTS is the revised, fuller sibling: the same Economic Indicators Time Series query surface at with data_type_code distinguishing sales, inventories and inventory-to-sales ratios rather than sales alone. That makes it the working-capital source — one row per kind of business per month per measure per adjustment flag, across dozens of retail categories spanning decades of history. The kind-of-business list includes NAICS 444 building material and supplies dealers plus furniture and home furnishings stores lines, so a single category_code filter yields a DIY-demand panel. Two checks before production: confirm the exact data_type_code values for inventories and inventory-to-sales ratios against the MRTS documentation, and pin per-category series start dates, which the metadata files do not expose.
Can you parse Home Depot filings into a fundamentals pipeline?
For pipelines, skip the PDFs and go to EDGAR. enumerates the filing index by accession number, form type and date — recent forms include 97 8-Ks and 25 10-Qs — and >.json returns individual XBRL concepts. SEC fair-access policy requires a declared User-Agent and holds data.sec.gov to roughly 10 requests per second. Filings are public records; the IR site's copy and imagery remain The Home Depot's. Store counts and sales-by-department tables sit inside the 10-K rather than on the landing page, and their page numbers shift year to year.
Straight answers
Is there a financial time series API for backtesting home improvement retail strategies?
Not an intraday one. The Census APIs publish monthly national series — MARTS advance estimates about two weeks after each month closes, MRTS revised values with inventories and inventory-to-sales ratios — so the cadence suits nowcasting and monthly strategy research.
What alternative data works for quantitative research on home improvement retail?
Demand-side signals dominate, because the slice holds no clickstream or transaction-level corpus. MARTS's early release acts as a nowcast input roughly two weeks before revised MRTS values land, and both split by seasonal adjustment.
Where to get training data for home improvement retail models?
Match the target. Demand nowcasters train on MARTS's roughly 40-50 category series per release, filtering category_code to building material and garden equipment dealers. Inventory and working-capital models use MRTS's three measures per kind of business.
Rows before rollout
Sample rows from any shelf entry — the field dictionary and coverage notes ride along. If the shelf misses what you need, say so; sourcing requests are half our job.
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