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Sampling Observations — String Normalisation + Duplicate Key Report
x402
Sampling Observations — String Normalisation + Duplicate Key Report 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 sampling observation records: string normalisation of text fields and duplicate key detection, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — String normalisation + Duplicate key report: String normalisation + Duplicate key report 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 structured reports: (1) a string normalisation report identifying and correcting inconsistent text values in fields like dataset_group across submitted rows; (2) a duplicate key report listing any row_id values that appear more than once. Both reports cover up to 200 input rows and are generated using local analytical engines with no external lookups.
Example use cases
Deduplicating survey sample records
“I have 120 rows of survey sampling data with row_id, date, sample_value, and sample_weight — can you check for any duplicate row IDs and flag them for me?”
Normalising dataset group labels before aggregation
“Before I aggregate my sampling observations, can you normalise the dataset_group strings across these 80 rows so inconsistent capitalisation or spacing doesn't cause mismatches?”
Pre-pipeline data quality check on sampling exports
“I'm about to load 150 sampling observation records into our pipeline — can you run a duplicate key report and string normalisation check on them first so I know the data is clean?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-021?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 sampling observation records (with sample_value and sample_weight fields) and need both string normalisation and duplicate key detection in a single low-cost call ($0.01 USDC). It is ideal for pre-pipeline data quality checks on survey or measurement datasets where row uniqueness and consistent text labels matter. Prefer alternatives if you need outlier detection, statistical summaries, pivot tables, or more than 200 rows.
Side effects
- Input array is empty or exceeds 200 rows — request rejected
- Rows missing required fields (row_id, date, sample_value, sample_weight) — validation error
- Date field does not match YYYY-MM-DD pattern — schema rejection
- sample_value or sample_weight outside allowed numeric range — rejection
- Malformed JSON body — parse error
- Payment not included or insufficient — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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