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Join Coverage — Grouped Numeric Summary + Category Frequencies
x402
Join Coverage — Grouped Numeric Summary + Category Frequencies 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).
Computes grouped numeric summary statistics and category frequency distributions for join coverage records (matched_rows, source_rows) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Grouped numeric summary + Category frequencies: Grouped numeric summary + Category frequencies for supplied join coverage records (matched_rows, source_rows). 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 grouped numeric summary (e.g. mean, min, max, std dev) of the selected field (matched_rows or source_rows) broken down by dataset_group, and (2) category frequency counts showing how often each dataset_group appears across the supplied rows. Results are computed locally with no external lookups.
Example use cases
ETL pipeline join coverage audit
“I ran a nightly ETL job and collected join coverage stats — matched_rows and source_rows — for dataset groups 'customers' and 'orders' across the past week. Can you compute a grouped numeric summary and category frequency breakdown for matched_rows so I can see how each group is performing?”
Data warehouse match rate analysis
“I have join coverage data from our data warehouse reconciliation for groups 'transactions' and 'refunds' across 10 dates in November 2026. Please give me grouped summary statistics and category frequencies for source_rows so I can understand the distribution.”
Multi-group join quality reporting
“We track join coverage across four dataset groups daily — give me a numeric summary grouped by dataset_group and a frequency count of how often each group appears, using matched_rows as the analysis field, for the 50 rows I'm supplying.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-086?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular join coverage data (matched_rows, source_rows) segmented by dataset group and date, and need both grouped numeric descriptive statistics and category frequency distributions in a single call without any external data lookup or prediction. Ideal for ETL auditing, data quality monitoring, and reconciliation reporting workflows where you supply the data and want local analytical summaries fast and cheaply.
Side effects
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) returns validation error
- More than 200 rows submitted — request rejected due to maxItems constraint
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in numeric fields may affect summary statistics output
- Empty rows array rejected due to minItems: 1 constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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