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Price Basket Observations — String Normalisation + Date by Category Pivot
x402
Price Basket Observations — String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Runs two local analytical reports on price basket observation data: string normalisation and a date-by-category pivot, for up to 200 rows of item_price or quantity_weight records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Price basket observations — String normalisation + Date by category pivot: String normalisation + Date by category pivot 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 for the supplied price basket observation rows: (1) a string normalisation report cleaning and standardising text fields, and (2) a date-by-category pivot table grouping either item_price or quantity_weight values by date and region/category. No external data is fetched; all analysis runs locally on the supplied rows.
Example use cases
Regional price basket pivot analysis
“I have 150 rows of price basket observations with item prices across three regions and weekly dates — can you normalise the strings and pivot the data by date and category so I can see how prices vary across regions over time?”
Quantity weight distribution by category
“Take my basket records with quantity_weight values across multiple regions and dates and give me both reports: the string-normalised version and the date-by-category pivot, using the quantity_weight field.”
Economics data cleanup and summary
“I've got about 80 price basket rows for an economics report — each has a date, region, item price, and quantity weight. Can you normalise the text fields and produce a date-by-category pivot for item_price so I can spot patterns by region?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-economics-07-035?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of price basket observation data (with item_price and quantity_weight fields) and need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for offline, local analytical processing of economics or retail basket data without any live lookups or predictions. Prefer it over general-purpose analytics tools when you need these two specific report types bundled together cheaply.
Side effects
- Rows array is empty or exceeds 200 items — validation error returned
- Invalid date format (not YYYY-MM-DD) in any row — schema validation failure
- item_price or quantity_weight values outside allowed numeric range — rejection
- Missing required fields (row_id, region, date) on any row — schema error
- Invalid field selector (not 'item_price' or 'quantity_weight') — enum validation error
- Payment not provided or insufficient USDC — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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