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Join Coverage Analytics — Exact Row Deduplication + Two-Measure Correlation
x402
Join Coverage Analytics — Exact Row Deduplication + Two-Measure Correlation 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).
Deduplicates exact rows and computes correlation between matched_rows and source_rows measures for up to 200 join coverage records, delivering two analytical reports in a single call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Exact row deduplication + Two-measure correlation: Exact row deduplication + Two-measure correlation 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) an exact row deduplication report identifying and removing duplicate rows from the submitted join coverage records, and (2) a two-measure Pearson or equivalent correlation report quantifying the statistical relationship between matched_rows and source_rows across the supplied dataset. Both reports are computed locally on the submitted data with no external lookups.
Example use cases
ETL pipeline join quality audit
“I've got 50 rows of join coverage data from my ETL pipeline with matched_rows and source_rows per dataset group and date — please deduplicate any exact duplicate rows and tell me how correlated matched_rows and source_rows are across the whole dataset.”
Data warehouse coverage anomaly detection
“Can you run exact row deduplication and a two-measure correlation between matched_rows and source_rows on these 120 join coverage records from my data warehouse? I want to know if there are duplicate entries and how tightly the two counts track each other.”
Multi-group join coverage comparison
“I have join coverage records from three dataset groups over the past month — about 80 rows total with matched_rows and source_rows for each date. Can you deduplicate them and compute a correlation between those two measures so I can see if higher source row counts predict higher match rates?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-050?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both exact row deduplication and a two-measure correlation on join coverage data (matched_rows vs source_rows) in a single low-cost call. It is ideal for data engineering and ETL quality checks where you need to clean duplicates and quantify the relationship between match counts and source counts simultaneously, without sending data to an external ML or analytics platform. Prefer this over general-purpose analytics services when your data is already structured with row_id, dataset_group, date, matched_rows, and source_rows fields and you want deterministic local computation at minimal cost.
Side effects
- Fewer than 1 or more than 200 rows submitted — validation error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — schema validation failure
- Date not matching YYYY-MM-DD format — pattern validation error
- Numeric values outside allowed range (±1,000,000,000,000) — validation rejection
- All rows are identical (degenerate deduplication case) — may return trivial deduplication result
- Insufficient variance in matched_rows or source_rows for meaningful correlation — correlation may return NaN or undefined
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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