Join Coverage Two-Measure Correlation and Missing-Value Fill 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).
Computes Pearson correlation between matched_rows and source_rows join coverage metrics, and fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 supplied rows.
Join coverage — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill 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.
Two structured analytical reports: (1) a Pearson correlation result between matched_rows and source_rows across the supplied dataset, and (2) a version of the chosen measure field with explicit missing-value fills applied using the specified method (zero, mean, or median). Results are computed locally from the supplied data with no external lookups.
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-184?utm_source=zero.xyzChoose this endpoint when you have tabular join coverage data with matched_rows and source_rows columns and need both a correlation analysis and missing-value imputation in a single call without external data lookups. It is purpose-built for data engineering and ETL quality workflows where you want local statistical computation on supplied data at low cost. Prefer alternatives if you need more than two measures analyzed simultaneously, more than 200 rows processed, or external data sources consulted.
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
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