costinflation/ground-beef-prices-raw-dataset-2026

18,928 raw U.S. ground beef price observations across 12 ZIP markets and 29 days.

Ground Beef Prices Raw Dataset (2026)

Analyze 18,928 unaggregated product-level listed retail prices for raw ground beef and beef patties 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	18,928
Columns	16
Observation window	July 13–August 10, 2026
Dates / ZIP markets	29 / 12
Market-days	348 of 348
Distinct product titles	100
Comparable-price rows	16,412 (86.7%)
Rows with unresolved comparison	2,516 (13.3%)
Comparison target	1 pound
Format / currency	CSV / USD
Expected updates	None; fixed research snapshot

A result worth investigating

The P90 comparable price was 3.0× the P10. Across compatible rows, the 1 pound-equivalent price ranged from a P10 of $7.33 to a P90 of $21.88, a 3.0× spread. This is a distribution description, not a matched-product quality or value claim.

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 comparison does not adjust for fat percentage, seasoning, form, or product quality. 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 ground-beef prices
• Track matched product titles through time
• Compare selected ZIP markets
• Build a reproducible retail-price dashboard
• Run reproducible EDA and missing-value analysis

Quick start with Pandas

import pandas as pd

df = pd.read_csv(
    "costinflation-ground-beef-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 28 byte-identical input repeats.
• Scope review excluded 0 definite out-of-scope or unsafe titles representing 0 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). Ground Beef Prices Raw Dataset (2026). CC0 1.0 Universal.

Resources

• Ground beef price history
• Kaggle dataset
• Hugging Face dataset

Released by CostInflation Team.