A clean, normalized, 1P-verified retail product catalog covering major US retailers (Walmart and Target). Designed for data scientists, machine learning engineers, retail arbitrageurs, and e-commerce developers.
Most scraped retail catalogs online are messy:
- Barcode leading zeros are truncated (078742...becomes78742...).
- 404 dead links and spam 3P marketplace vendors.
- Cluttered with tracking tokens and session IDs.
This dataset provides institutional-grade clean data:
- 100% 1P Verified: Only authentic first-party retail items sold directly by Walmart and Target.
- Preserved UPC/GTIN Barcodes: Formatted as strict strings with UTF-8 BOM to prevent Excel truncation.
- Clean Canonical URLs: Direct storefront links with zero tracking tokens.
- Normalized Schema: Cleaned brands, categories, prices, and stock indicators.
A free 100-row preview sample is included in this repository: free_sample_preview_100_rows.csv.
Looking for the complete production database for your application or business?
What's inside the full package:
- Complete 50k+ unified cross-referenced table in CSV (UTF-8 BOM).
- Streaming JSONL file for big-data pipelines (BigQuery, Pandas, Elasticsearch).
- Pre-indexed SQLite 3 database with B-Tree indexes on upc_gtin,brand, andcategory.
- Full commercial use license.
Run the included quickstart.py to inspect the sample data:
import csv
with open("free_sample_preview_100_rows.csv", mode="r", encoding="utf-8-sig") as f:
reader = csv.DictReader(f)
for row in list(reader)[:5]:
print(f"[{row['retailer']}] {row['brand']} - {row['title']} (UPC: {row['upc_gtin']})")- The free sample dataset in this repository is licensed under the MIT License.
- The full master catalog on Gumroad includes a Perpetual Commercial Use License.