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Join Coverage Analytics: Numeric Distribution + Date-by-Category Pivot
x402
Join Coverage Analytics: Numeric Distribution + 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 2026-10-23).
Generates two local analytical reports — a numeric distribution and a date-by-category pivot — for join coverage records containing matched_rows and source_rows fields, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot 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 computed locally from the supplied data: (1) a numeric distribution of the selected field (matched_rows or source_rows) showing statistical spread across records, and (2) a date-by-category pivot aggregating the selected field by date and dataset_group. No external lookups are performed; results are derived entirely from the submitted rows.
Example use cases
ETL pipeline join quality audit
“I have 80 records from my ETL pipeline join step with dataset groups like 'customers' and 'orders', each with a date, matched_rows, and source_rows. Can you run a numeric distribution and date-by-category pivot on matched_rows so I can see how well rows are matching across groups over time?”
Data warehouse coverage comparison
“I want to compare join coverage across my data warehouse partitions — I have up to 200 rows with dataset_group, date, source_rows, and matched_rows. Please give me both a numeric distribution and a date-by-category pivot on source_rows.”
Daily join match rate trend analysis
“Can you analyze my join coverage records from the last quarter — about 120 rows tagged by dataset_group and date, with matched_rows and source_rows counts — and produce a numeric distribution plus a category-by-date pivot so I can spot which groups have low match rates on which days?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-083?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have join coverage data (matched_rows and source_rows per record) and need two quick analytical reports — a numeric distribution and a date-by-category pivot — computed locally without any external data lookups. Ideal for small-to-medium datasets (up to 200 rows) where you want cheap ($0.01 USDC for both reports), self-contained analytics on dataset group join quality over time.
Side effects
- Fewer than 1 row submitted — request rejected
- More than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — schema validation error
- Numeric values outside allowed range (±1,000,000,000,000) — rejected
- Invalid field enum value (not matched_rows or source_rows) — rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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