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Join Coverage Analytics — Exact Row Deduplication + Date by Category Pivot
x402
Join Coverage Analytics — Exact Row Deduplication + 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).
Runs two analytical reports on join coverage data: exact row deduplication and a date-by-category pivot table, for up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Exact row deduplication + Date by category pivot: Exact row deduplication + 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
Returns two analytical reports: (1) a deduplicated version of the input rows after removing exact duplicate records, and (2) a pivot table of the selected metric field (matched_rows or source_rows) broken out by date on one axis and dataset_group on the other, enabling cross-group temporal analysis of join coverage.
Example use cases
Deduplicating ETL join coverage audit logs
“I've got a batch of join coverage records from our ETL pipeline — some rows are exact duplicates. Can you deduplicate them and also pivot the matched_rows counts by date and dataset group so I can see coverage trends? Here are the rows with row_id, dataset_group, date, matched_rows, and source_rows.”
Daily coverage pivot for multi-group data reconciliation
“Can you take my join coverage data for groups 'sales' and 'returns' across October 2026, deduplicate any exact row duplicates, and give me a pivot of source_rows by date and category?”
Pre-report data cleanup for join quality dashboard
“Before I build my dashboard, I need to clean up these join coverage records — remove any exact duplicate rows and pivot the matched_rows field by date and dataset group. I have about 150 rows with the standard fields.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-052?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 join coverage records and need both exact row deduplication and a date-by-category pivot in a single call. It is purpose-built for join coverage metrics (matched_rows, source_rows) and is more efficient than running two separate analytics steps. Prefer it over generic data tools when you need a combined clean+pivot report without any live lookup or external data enrichment.
Side effects
- Input array is empty or exceeds 200 rows — validation error returned
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- field enum value not one of 'matched_rows' or 'source_rows' — rejected
- row_id or dataset_group exceeds 80 character limit — field truncation or rejection
- Payment of 0.01 USDC not completed via x402 protocol — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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