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Join Coverage IQR Outlier Flags + Two-Measure Correlation Analyzer
x402
Join Coverage IQR Outlier Flags + Two-Measure Correlation Analyzer 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 IQR-based outlier detection and two-measure Pearson/rank correlation on up to 200 join coverage records (matched_rows, source_rows), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Join coverage — IQR outlier flags + Two-measure correlation: IQR outlier flags + 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
Two independent analytical reports: (1) IQR outlier flags for each row indicating whether the selected field (matched_rows or source_rows) falls outside the interquartile range boundaries, including computed Q1/Q3/IQR thresholds; (2) a two-measure correlation report quantifying the statistical relationship between matched_rows and source_rows across the supplied records, including the correlation coefficient and relevant summary statistics. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
ETL pipeline join quality audit
“I'm auditing our ETL pipeline and want to check if any of our daily join coverage records look like outliers — here are 30 rows with matched_rows and source_rows across two dataset groups (orders and customers), can you run IQR outlier flagging and also correlate matched_rows against source_rows for me?”
Data drift detection across dataset groups
“We've noticed some weirdness in our join rates lately — can you take these 50 join coverage records from the last two months and tell me which matched_rows values are IQR outliers, plus show me how correlated matched_rows and source_rows are across our 'transactions' and 'accounts' groups?”
Pre-release data quality gate check
“Before we release this dataset, I need a quick statistical sanity check — run IQR outlier detection on source_rows for these 80 join coverage records and also compute the two-measure correlation between matched_rows and source_rows so I know if there's a systematic issue.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-09-176?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured join coverage records with matched_rows and source_rows fields and need both IQR-based outlier detection and a correlation report in a single call at minimal cost. Ideal for data engineers and analytics pipelines that need lightweight, self-contained statistical QA on join metrics without spinning up a full analytics environment. Prefer this over generic stats APIs when your data already conforms to the join-coverage schema (row_id, dataset_group, date, matched_rows, source_rows) and you want two reports bundled for $0.01.
Side effects
- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows submitted — exceeds maxItems limit and will be rejected
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row
- Date field not matching YYYY-MM-DD pattern — validation error
- Null values in both measure columns may degrade or invalidate correlation computation
- Payment of 0.01 USDC not completed — x402 payment required before response
- Insufficient variance in data (e.g. all identical values) may produce degenerate IQR or correlation results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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