README.md

metadata

license: cc0-1.0
language:
  - en
task_categories:
  - tabular-regression
tags:
  - retail
  - prices
  - time-series
  - raw-data
  - food
pretty_name: Onion Prices Raw Dataset (2026)
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: costinflation-onion-retail-prices-raw-2026-07-13-to-2026-08-10.csv
dataset_info:
  features:
    - name: series_id
      dtype: string
    - name: series_title
      dtype: string
    - name: canonical_url
      dtype: string
    - name: geography_type
      dtype: string
    - name: geography_id
      dtype: string
    - name: geography_label
      dtype: string
    - name: observed_date
      dtype: string
    - name: product_name
      dtype: string
    - name: quantity_value
      dtype: float64
    - name: quantity_unit
      dtype: string
    - name: quantity_name
      dtype: string
    - name: price_amount
      dtype: float64
    - name: currency_code
      dtype: string
    - name: normalized_price_amount
      dtype: float64
    - name: normalized_quantity_value
      dtype: float64
    - name: normalized_quantity_unit
      dtype: string
  splits:
    - name: train
      num_examples: 17274

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

Field	Coverage
Rows	17,274
Columns	16
Observation window	July 13–August 10, 2026
Dates / ZIP markets	29 / 12
Market-days	348 of 348
Distinct product titles	92
Comparable-price rows	12,130 (70.2%)
Rows with unresolved comparison	5,144 (29.8%)
Comparison target	1 pound
Format / currency	CSV / USD
Expected updates	None; fixed research snapshot

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

Column	Type	Meaning
series_id	string	Stable source-neutral dataset series key
series_title	string	Human-readable series title
canonical_url	string	Related CostInflation category page
geography_type	string	Geography level; always postal_code
geography_id	string	Five-digit U.S. ZIP code; load as text
geography_label	string	Human-readable ZIP-market label
observed_date	date	Observation date in YYYY-MM-DD
product_name	string	Full observed title; not a stable product ID
quantity_value	number	Resolved package quantity; 0 if unresolved
quantity_unit	string	Resolved package unit or unknown
quantity_name	string	Human-readable package quantity
price_amount	number	Listed package or unit price
currency_code	string	Currency; always USD
normalized_price_amount	nullable number	Listed price scaled to the dataset comparison target
normalized_quantity_value	number	Numeric comparison target
normalized_quantity_unit	string	Unit for the comparison target

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

• Onions price history
• Kaggle dataset
• Hugging Face dataset

Released by CostInflation Team.