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Join Coverage Analytics: Weighted Mean + Dataset Comparison
x402
Join Coverage Analytics: Weighted Mean + Dataset Comparison 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 a secondary-measure weighted mean and performs a keyed dataset comparison for join coverage records (matched_rows, source_rows) across two supplied datasets.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — Secondary-measure weighted mean + Keyed dataset comparison: Secondary-measure weighted mean + Keyed dataset comparison 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 independent analytical reports: (1) a secondary-measure weighted mean of the selected field (matched_rows or source_rows), where the other measure acts as the weight, computed over the supplied rows; and (2) a keyed dataset comparison between the primary rows and the secondary 'other' rows, identifying differences by row_id, dataset_group, and date. Both reports are computed locally with no external data access.
Example use cases
ETL pipeline join quality audit
“I have two runs of our ETL pipeline producing join coverage stats — each with row_id, dataset_group, date, source_rows, and matched_rows. Can you compute the weighted mean of matched_rows for both runs and compare them side by side to see where coverage diverged?”
Dataset group coverage drift detection
“We track join coverage daily across group-a and group-b. Here are this week's records and last week's records — can you compute the source-row-weighted mean of matched_rows for each dataset and flag where the two differ significantly?”
Data migration coverage validation
“After migrating our data warehouse, I want to verify that matched_rows counts are consistent before and after. I have two sets of up to 200 rows with row_id, date, dataset_group, source_rows, and matched_rows — run a weighted mean and keyed comparison on both, please.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-186?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need both a weighted mean calculation and a keyed side-by-side dataset comparison for join coverage data (matched_rows, source_rows) in a single $0.01 call, without needing live lookups or external enrichment. It is ideal for data engineers validating ETL join quality, comparing pipeline runs, or auditing coverage drift across dataset groups with up to 200 rows.
Side effects
- Fewer than 1 row supplied returns a validation error
- More than 200 rows supplied exceeds the row limit
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) causes schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Null values in both matched_rows and source_rows may produce undefined weighted mean results
- Mismatched keys between primary and secondary datasets may result in sparse comparison output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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