costinflation/period-underwear-prices-raw-dataset-2026
44,386 raw U.S. period underwear price observations across 12 ZIP markets and 29 days. Period Underwear Prices Raw Dataset (2026) Analyze 44,386 unaggregated product-level listed retail prices for period underwear 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… See the full description on the dataset page: https://huggingface.co/datasets/costinflation/period-underwear-prices-raw-dataset-2026.
44,386 raw U.S. period underwear price observations across 12 ZIP markets and 29 days.
Period Underwear Prices Raw Dataset (2026)
Analyze 44,386 unaggregated product-level listed retail prices for period underwear 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
60.2% of rows expose a quantity-cleaning challenge. Only 17,652 of 44,386 rows (39.8%) have a compatible resolved garment count for the 1 garment 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. These are listed retail prices—not sales, orders, revenue, demand, inventory, market share, or consumer behavior. Multiple distinct offers can share a title, ZIP, and date; exact duplicate public rows have been removed.
Comparable-price method
The fixed comparison target is 1 garment. Only count-compatible packages normalize to one garment; multipacks and kits without a resolved count remain blank. The original package price and quantity remain in every row, so users can audit or replace the provided comparison.
Columns
Project ideas
- Measure the effect of unresolved multipack counts
- Compare one-garment-equivalent prices
- Track matched product titles through time
- Build an apparel data-cleaning benchmark
- Run EDA in Python, R, SQL, Excel, Tableau, or Power BI
- Benchmark missing-value handling without discarding listed-price observations
Quick start with Pandas
import pandas as pd
df = pd.read_csv(
"costinflation-period-underwear-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 4,905 byte-identical input repeats.
- Scope review excluded 1 definite out-of-scope or unsafe titles representing 12 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). Period Underwear Prices Raw Dataset (2026). CC0 1.0 Universal.
Resources
- Period underwear price history
- The matching Hugging Face or Kaggle release will be linked after both destinations are verified.
Released by CostInflation Team.