Datasets:

costinflation
/

multivitamin-prices-raw-dataset-2026

license: cc0-1.0
language:
  - en
task_categories:
  - tabular-regression
tags:
  - retail
  - prices
  - time-series
  - raw-data
  - supplements
pretty_name: Multivitamin Prices Raw Dataset (2026)
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: >-
          costinflation-multivitamin-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: 8167

8,167 raw U.S. multivitamin price observations across 12 ZIP markets and 29 days.

Multivitamin Prices Raw Dataset (2026)

Analyze 8,167 unaggregated product-level listed retail prices for solid-unit multivitamin supplements 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	8,167
Columns	16
Observation window	July 13–August 10, 2026
Dates / ZIP markets	29 / 12
Market-days	348 of 348
Distinct product titles	119
Comparable-price rows	7,634 (93.5%)
Rows with unresolved comparison	533 (6.5%)
Comparison target	100 units
Format / currency	CSV / USD
Expected updates	None; fixed research snapshot

A result worth investigating

The P90 comparable price was 7.9× the P10. Across compatible rows, the 100 units-equivalent price ranged from a P10 of $5.25 to a P90 of $41.58, a 7.9× 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 units. Compatible count units normalize to 100 units. Ingredient profiles, strength, formulation, safety, and efficacy are not treated as equivalent; this is not medical advice. 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 package-count prices without nutrient adjustment
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-multivitamin-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 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). Multivitamin Prices Raw Dataset (2026). CC0 1.0 Universal.

Resources

Released by CostInflation Team.