costinflation/onion-prices-raw-dataset-2026
17,274 raw U.S. onion price observations across 12 ZIP markets and 29 days. Onion Prices Raw Dataset (2026) Analyze 17,274 unaggregated product-level listed retail prices for fresh common onions across 12 U.S. ZIP markets from July 13 through August 10, 2026. The single analysis-ready CSV preserves titles, dates, geography, package quantities, listed prices, and a source-neutral comparable-price field. What “raw” means here: unaggregated product-level observations after… See the full description on the dataset page: https://huggingface.co/datasets/costinflation/onion-prices-raw-dataset-2026.
17,274 raw U.S. onion price observations across 12 ZIP markets and 29 days.
Onion Prices Raw Dataset (2026)
Analyze 17,274 unaggregated product-level listed retail prices for fresh common onions across 12 U.S. ZIP markets from July 13 through August 10, 2026. The single analysis-ready CSV preserves titles, dates, geography, package quantities, listed prices, and a source-neutral comparable-price field.
What “raw” means here: unaggregated product-level observations after scope and safety filtering. The file includes derived normalization fields; it is not untouched acquisition data.
Dataset at a glance
A result worth investigating
29.8% of rows expose a quantity-cleaning challenge. Only 12,130 of 17,274 rows (70.2%) have a compatible resolved fresh-onion mass for the 1 pound comparison. The unresolved rows remain in the file with their listed prices and a blank comparable-price field, making missingness an explicit analysis surface.
What one row represents
One row is one quality-filtered product-title, ZIP-market, date, package-quantity, and listed-price observation. It is not a sale, order, demand, inventory, market-share, or consumer record. Distinct offers may share a title, ZIP, and date; exact duplicate public rows are removed.
Comparable-price method
The fixed comparison target is 1 pound. Compatible mass units normalize to one pound. The public scope is fresh common onions; preserved onions, planting products, green onions, and shallots are excluded during exact-title review. Original package fields remain available for audit.
Columns
Project ideas
- Compare one-pound-equivalent fresh-onion prices
- Track matched product titles through time
- Run reproducible EDA and missing-value analysis
Quick start with Pandas
import pandas as pd
df = pd.read_csv(
"costinflation-onion-retail-prices-raw-2026-07-13-to-2026-08-10.csv",
dtype={"geography_id": "string"},
)
comparable = df.dropna(subset=["normalized_price_amount"]).copy()
print(comparable["normalized_price_amount"].describe())Quality and limitations
- All 348 expected date × ZIP-market combinations are present.
- Exact duplicate public rows: 0. The preparation pass removed 0 byte-identical input repeats.
- Scope review excluded 25 definite out-of-scope or unsafe titles representing 5,179 input rows.
- Product titles are descriptive text, not stable public product identifiers.
- ZIP labels describe selected markets, not citywide estimates; the panel is not nationally representative.
- Availability and title wording can change unmatched aggregates through assortment change.
- Shipping, tax, redeemed promotions, purchases, and product performance are outside the dataset.
License
Released under CC0 1.0 Universal for unrestricted reuse. Attribution is not required, but citation helps others find the release.
CostInflation Team. (2026). Onion Prices Raw Dataset (2026). CC0 1.0 Universal.
Resources
Released by CostInflation Team.