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Document Approvals Two-Measure Correlation and Missing-Value Fill
x402
Document Approvals 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 2026-11-02).
Computes Pearson correlation between submitted_documents and approved_documents, and fills missing values using zero, mean, or median imputation — delivering two statistical reports for up to 200 document approval records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Document approvals — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied document approvals records (submitted_documents, approved_documents). 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 Pearson or equivalent two-measure correlation result between submitted_documents and approved_documents across the supplied rows, and (2) a dataset with missing values in the specified field filled using the chosen method (zero, mean, or median). Results are computed locally with no external lookups.
Example use cases
Approval rate correlation across teams
“I've got daily records for 4 team groups showing how many documents were submitted and how many got approved — can you calculate the correlation between submitted_documents and approved_documents and also fill any missing submitted_documents values using the mean?”
Missing data cleanup for approval dashboard
“Our document approval tracker has some null values in the approved_documents column — can you fill those blanks using median imputation and also give me the correlation between submitted and approved counts across all rows?”
Statistical QA on document pipeline data
“I need two reports on this batch of 150 document approval records: first, compute the correlation between submitted_documents and approved_documents; second, fill any missing approved_documents values with zero so the dataset is complete.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-17-184?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular document approval data (submitted vs approved counts per team/date) and need both a correlation analysis and missing-value imputation in a single call for up to 200 rows. It is especially useful when you want two distinct analytical outputs from shared input data without building your own statistical pipeline. Not suitable for live document system queries, approval predictions, or datasets exceeding 200 rows.
Side effects
- Fewer than 1 row provided — minimum item count not met
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, submitted_documents, approved_documents) on any row
- Invalid date format not matching YYYY-MM-DD pattern
- Invalid enum value for method or field parameters
- Payment not completed — x402 payment required before response
- All values null in target field — imputation has no non-null reference for mean/median
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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