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Sampling Observations — String Normalisation + Numeric Row Ordering
x402
Sampling Observations — String Normalisation + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Normalises string fields and applies numeric row ordering to sampling observation records (sample_value, sample_weight) for up to 200 rows, returning 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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: (1) a string normalisation report covering dataset_group and related string fields, and (2) a numeric row ordering report for the selected field (sample_value or sample_weight), applied across up to 200 supplied sampling observation rows.
Example use cases
Ordering survey sample data numerically
“I have 50 survey sampling records with sample_value and sample_weight columns. Can you normalise the string fields like dataset_group and then order all rows numerically by sample_value? Here are the rows in JSON format with row_id, date, dataset_group, sample_value, and sample_weight filled in.”
Cleaning lab measurement group labels
“My lab has 120 sampling observation rows and the dataset_group labels are inconsistently cased and formatted. Can you run string normalisation on them and also give me a numeric row ordering report based on the sample_weight field?”
Auditing weighted sample ordering for QA
“I need to QA my sampling dataset — can you normalise the string columns and produce a numeric ordering of the rows by sample_value so I can spot outliers? I'll send up to 180 rows with row_id, date, dataset_group, sample_value, and sample_weight.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-025?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 sampling observation records (with sample_value and sample_weight) and need both string normalisation on group/label fields and a numeric row ordering report in a single low-cost call. It is ideal for pre-processing or QA of sampling datasets without needing live data lookup, prediction, or external integrations.
Side effects
- More than 200 rows submitted — request rejected due to maxItems limit
- Missing required fields (row_id, dataset_group, date, sample_value, or sample_weight) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — validation error
- Empty rows array (minItems=1 violated) — rejected
- Invalid field selector (must be '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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