Reference Reference tableQC clean AI-training-safe

US SNAP

Every US retailer authorized to accept SNAP (food-stamp) benefits - ~254k stores - in one clean, geocoded table. USDA's Food and Nutrition Service exposes it as a paginated ArcGIS service; we page the whole layer and ship one fat row per store: name, store type, full address, county and lat/lon. A clean, open food-access / retail-footprint POI set - the kind of location data usually sold by scrapers, here authoritative and public domain. Owner/grantee personal-name field dropped (no PII).

254K
rows
11
columns
21.5 MB
download
Source
USDA FNS
Licence
Redistributable open data
Quality
QC clean · 0 failures
Format
Apache Parquet + dictionary

Safe to train on

Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.

What's included

  • ~254k SNAP-authorized US retailers - one clean, geocoded row per store
  • Store name, store type, full street address, city/state/ZIP, county, lat/lon
  • Open food-access / retail-footprint POI - authoritative alternative to scraped store data
  • Business locations only - owner/grantee personal name dropped (no PII)
  • Audiences: grocery/retail site-selection, food-desert research, CPG distribution, proptech
  • Public domain (USDA FNS) - free commercial reuse & resale
  • Source: U.S. Department of Agriculture, Food and Nutrition Service - SNAP Retailer Locator

Schema

ColumnTypeDescriptionFilledDistinct
record_id int USDA SNAP retailer record id (primary key) 100.0% 254,048
store_name str Store name 100.0% 242,981
store_type str Store type (Supermarket, Convenience Store, Grocery Store, …) 100.0% 8
street_address str Street address 100.0% 244,061
address_2 str Additional address line 6.5% 3,502
city str City 100.0% 16,338
state str US state 100.0% 53
zip str ZIP code 100.0% 24,011
county str County 100.0% 1,839
latitude float Latitude 100.0% 241,905
longitude float Longitude 100.0% 240,201

Sample & preview

Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: USDA FNS (redistributable open data; attribution passes through - see our Licence).

Don't trust screenshots - drop the sample into your notebook right now.

import pandas as pd
df = pd.read_parquet("us-snap-retailers_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join
⬇ Download free Parquet sample or CSV for Excel