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Replenishment Timing Two-Measure Correlation and Missing-Value Fill
x402
Replenishment Timing 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 2026-10-29).
Computes Pearson correlation between lead_days and received_units, and fills missing values using zero, mean, or median imputation, for up to 200 replenishment timing rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Replenishment timing — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied replenishment timing records (lead_days, received_units). 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 two-measure correlation report showing the statistical relationship between lead_days and received_units, and (2) an explicit missing-value fill report where null values in the specified field are replaced using zero, mean, or median imputation. Covers up to 200 supplied rows.
Example use cases
Supply chain lead time correlation
“I've got replenishment data for two store groups over the past quarter — can you correlate lead_days with received_units across all 120 rows and tell me how strong the relationship is?”
Missing inventory data imputation
“My replenishment dataset has about 30 missing received_units values across 180 rows — can you fill them using mean imputation and give me the corrected dataset?”
Multi-store replenishment audit
“I need two reports on my store replenishment records: a correlation between lead days and received units, and a median fill for any missing lead_days — the dataset has entries for group-a and group-b across 90 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-12-184?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need lightweight, offline statistical analysis of replenishment timing data — specifically a Pearson-style two-measure correlation and missing-value imputation — without requiring a live database connection, external prediction model, or professional assessment. Ideal for small-to-medium batches (up to 200 rows) of retail supply chain records where lead time and received quantity data may be incomplete.
Side effects
- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, date, lead_days, received_units) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Both lead_days and received_units entirely null — correlation cannot be computed
- Invalid method enum value (not zero/mean/median) causes schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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