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Sampling Observations — String Normalisation + Secondary-Measure Weighted Mean
x402
Sampling Observations — String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Performs string normalisation and secondary-measure weighted mean analytics on up to 200 supplied sampling observation records (sample_value, sample_weight), returning 2 independent local reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied sampling observations records (sample_value, sample_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 2 analytical reports computed locally: (1) a string normalisation report applied to the submitted observation records, and (2) a secondary-measure weighted mean computed from the sample_value and sample_weight fields across up to 200 rows, grouped by dataset_group and date.
Example use cases
Survey response weighted scoring
“I've got 150 survey rows, each with a respondent ID, a date, a numeric response value and a confidence weight — can you run string normalisation plus a weighted mean on the response values across all my dataset groups and return both analytical reports?”
Lab sample batch quality check
“Here are 80 lab sampling records grouped by experiment batch, each with a sample_value and a sample_weight measured on specific dates — please compute the secondary-measure weighted mean on sample_value and normalise the strings, and give me the two summary reports.”
Retail inventory sampling analysis
“I have daily inventory sampling observations for two store groups over the past month, up to 200 rows, with a sample_value for units and a sample_weight for store size — run the weighted mean on sample_value and the string normalisation report for me.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected sampling observation records (up to 200 rows) and need both string normalisation and a secondary-measure weighted mean computed together in a single paid call, without requiring any live data lookup, prediction, or external integrations. It is cost-effective at $0.01 USDC for two bundled reports.
Side effects
- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) — row-level validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- sample_value or sample_weight out of allowed numeric range (±1e12) — field validation error
- Empty rows array — minItems constraint violation
- Invalid field enum value (not 'sample_value' or 'sample_weight') — enum validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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