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Sampling Observations Analytics — Quality Audit, Deduplication & Grouped Summary
x402
Sampling Observations Analytics — Quality Audit, Deduplication & Grouped Summary 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).
Runs three analytical reports on sampling observation data: a record quality audit, exact row deduplication, and a grouped numeric summary — all in a single call for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Record quality audit + Exact row deduplication + Grouped numeric summary: Record quality audit + Exact row deduplication + Grouped numeric summary for supplied sampling observations records (sample_value, sample_weight). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent reports: (1) a record quality audit flagging nulls, format issues, and anomalies across the supplied rows; (2) an exact row deduplication report identifying and removing fully identical records; and (3) a grouped numeric summary (e.g. count, mean, min, max) of the chosen field (sample_value or sample_weight) broken down by dataset_group.
Example use cases
Survey data quality check before analysis
“I have a batch of 150 survey sampling records with row IDs, group labels, dates, sample values, and weights. Can you audit them for quality issues, remove exact duplicates, and give me a grouped numeric summary of sample_value by dataset group?”
Deduplication of lab observation records
“We collected 80 lab sampling observations across two groups and suspect some rows were entered twice. Run an exact deduplication, a quality audit, and a grouped summary on sample_weight so I can see if any groups are skewed.”
Grouped summary of weighted sample data
“I've got 200 rows of sampling observations tagged with dataset groups and dates. Can you do a record quality audit, flag exact duplicates, and give me grouped stats on sample_value to see how each group compares numerically?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-211?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need all three analytical operations — quality audit, deduplication, and grouped numeric summary — on sampling observation data in a single low-cost call. It is ideal for pre-analysis data hygiene on datasets up to 200 rows with sample_value and sample_weight fields. Prefer this over separate tools when you want bundled reports from shared local computation with no external lookups, predictions, or side effects.
Side effects
- Exceeding 200 rows causes a validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) causes schema rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Values outside the allowed numeric range (±1,000,000,000,000) are rejected
- Empty rows array returns an error
- Non-numeric values in sample_value or sample_weight fields cause parsing failures
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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