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costinflation/pantyliner-prices-raw-dataset-2026

25,466 raw U.S. pantyliner price observations across 12 ZIP markets and 29 days. Pantyliner Prices Raw Dataset (2026) Analyze 25,466 unaggregated product-level listed retail prices for disposable pantyliners 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/pantyliner-prices-raw-dataset-2026.

sourceHugging Facecc0-1.0updated 1mo agoView on Hugging Face
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25,466 raw U.S. pantyliner price observations across 12 ZIP markets and 29 days.

Pantyliner Prices Raw Dataset (2026)

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Analyze 25,466 unaggregated product-level listed retail prices for disposable pantyliners 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

FieldCoverage
Rows25,466
Columns16
Observation windowJuly 13–August 10, 2026
Dates / ZIP markets29 / 12
Market-days348 of 348
Distinct product titles205
Comparable-price rows22,715 (89.2%)
Rows with unresolved comparison2,751 (10.8%)
Comparison target100 liners
Format / currencyCSV / USD
Expected updatesNone; fixed research snapshot

A result worth investigating

The P90 comparable price was 5.3× the P10. Across compatible rows, the 100 liners-equivalent price ranged from a P10 of $5.91 to a P90 of $31.09, a 5.3× 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 100 liners. Compatible count units normalize to 100 liners; unresolved counts remain blank. Size, absorbency, and material are not treated as performance-equivalent. Original package fields remain available for audit.

Columns

ColumnTypeMeaning
series_idstringStable source-neutral dataset series key
series_titlestringHuman-readable series title
canonical_urlstringRelated CostInflation category page
geography_typestringGeography level; always postal_code
geography_idstringFive-digit U.S. ZIP code; load as text
geography_labelstringHuman-readable ZIP-market label
observed_datedateObservation date in YYYY-MM-DD
product_namestringFull observed title; not a stable product ID
quantity_valuenumberResolved package quantity; 0 if unresolved
quantity_unitstringResolved package unit or unknown
quantity_namestringHuman-readable package quantity
price_amountnumberListed package or unit price
currency_codestringCurrency; always USD
normalized_price_amountnullable numberListed price scaled to the dataset comparison target
normalized_quantity_valuenumberNumeric comparison target
normalized_quantity_unitstringUnit for the comparison target

Project ideas

  • —Compare 100-liner package-equivalent prices
  • —Track matched product titles through time
  • —Compare selected ZIP markets
  • —Run reproducible EDA and missing-value analysis

Quick start with Pandas

python
import pandas as pd

df = pd.read_csv(
    "costinflation-pantyliner-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 3 definite out-of-scope or unsafe titles representing 19 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). Pantyliner Prices Raw Dataset (2026). CC0 1.0 Universal.

Resources

Released by CostInflation Team.