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Sampling Observations — Record Quality Audit + Date-by-Category Pivot
x402
Sampling Observations — Record Quality Audit + 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 2026-10-24).
Runs two local analytical reports on up to 200 sampling observation rows: a record quality audit and a date-by-category pivot table, for sample_value or sample_weight.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot 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
Two analytical reports returned together: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed dates across the submitted rows; and (2) a pivot table summarizing the selected field (sample_value or sample_weight) broken down by date and dataset_group category. No external data is fetched; all analysis is performed locally on the supplied rows.
Example use cases
Pre-analysis data quality check
“I have a dataset of 150 sampling observations with fields row_id, dataset_group, date, sample_value, and sample_weight. Can you audit the record quality and also pivot sample_value by date and category so I can see data issues before I run my analysis?”
Weighted sample distribution review
“Before I submit my survey sample data for reporting, run a quality audit and date-by-category pivot on the sample_weight field — I've got about 80 rows with group labels and dates ranging across October 2026.”
Multi-group temporal sampling summary
“I collected sampling observations across two groups over 30 days. Can you check the record quality and give me a date-by-category breakdown of sample_value so I can spot any gaps or anomalies in the data?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-017?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a date-by-category pivot on sampling observation data in a single low-cost call. It is ideal for pre-processing checks on small-to-medium datasets (up to 200 rows) with sample_value and sample_weight fields grouped by category and date. Prefer it over separate audit or pivot tools when cost efficiency and co-located reports matter and no live external lookup or prediction is needed.
Side effects
- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) — validation error
- Date field not matching YYYY-MM-DD pattern — parse error
- Numeric values outside the allowed range (-1e12 to 1e12) — rejected
- Invalid field enum value (not sample_value or sample_weight) — error
- Payment not included or insufficient — x402 payment required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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