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Price Basket Observations — String Normalisation + Trailing Mean Series
x402
Price Basket Observations — String Normalisation + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Runs string normalisation and trailing mean series analysis on supplied price basket observation records (item_price, quantity_weight) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Price basket observations — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied price basket observations records (item_price, quantity_weight). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two analytical reports sharing local engines: (1) a string-normalised version of the supplied price basket observation records, and (2) a trailing mean series computed over the selected numeric field (item_price or quantity_weight) using the specified window size, covering up to 200 input rows.
Example use cases
Smoothing retail price survey data
“I have a week's worth of retail price basket survey data — 50 rows with item prices and quantity weights across regions. Can you normalise the strings and compute a trailing mean series with a window of 5 on the item_price field so I can spot trends?”
Cleaning regional pricing records
“We collected price basket observations from 3 regions over the past month — about 120 rows. Run string normalisation and a trailing mean window of 7 on quantity_weight so we can compare regional patterns cleanly.”
Preparing basket data for economics report
“I need two analytical reports on these 30 price basket rows — string normalisation plus a trailing mean series with window 4 targeting item_price. Dates run from 2026-09-01 to 2026-09-30, split across group-a and group-b regions.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-07-028?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to both clean/normalise string fields and compute a windowed trailing mean series on price basket observation data in a single low-cost call. Ideal for economics and retail analytics workflows requiring lightweight, offline analytical transformations on up to 200 rows without any live data lookup, prediction, or external side effects.
Side effects
- Exceeds 200 row limit — request rejected
- Invalid date format (must be YYYY-MM-DD) — validation error
- Missing required fields (row_id, region, date) — schema error
- Window size outside range 2–200 — validation error
- Field value not one of ['item_price','quantity_weight'] — enum error
- Null values in numeric fields may affect trailing mean computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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