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Recovery Objectives Adjacent Row Changes and Missing Value Fill
x402
Recovery Objectives Adjacent Row Changes 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 adjacent-row delta changes and fills missing values for recovery objective records containing target and observed minutes, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Recovery objectives — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied recovery objectives records (target_minutes, observed_minutes). 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 analytical reports: (1) an adjacent-row change report showing delta values between consecutive rows for the specified field (target_minutes or observed_minutes), and (2) an explicit missing-value fill report where null entries in the specified field are replaced using the chosen method (zero, mean, or median). Results are computed locally with no external lookups and cover up to 200 input rows.
Example use cases
Filling null recovery targets before reporting
“I have a dataset of daily recovery objectives with some null target_minutes entries — can you fill those missing values using the median method and also show me the adjacent row changes for target_minutes across my 150 rows?”
Comparing consecutive observed recovery times
“Can you analyze my recovery objectives records and compute the adjacent row differences for observed_minutes across control groups, and also fill any gaps using zero-fill? I have about 80 rows across two groups.”
Multi-group recovery trend cleanup
“I'm tracking recovery objectives for group-a and group-b over October and some observed_minutes are missing — please fill them with the mean and also give me the row-to-row change report for observed_minutes across all 40 rows.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-security-20-162?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both adjacent-row delta computation and missing-value imputation for recovery objective records in a single low-cost call. It is best suited for small-to-medium datasets (up to 200 rows) where you want offline, deterministic analysis with no external dependencies. Prefer this over generic analytics tools when your data specifically involves target_minutes and observed_minutes fields for named control groups across dates, and you want two pre-packaged reports for $0.01.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, target_minutes, observed_minutes) causes schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Unrecognized method or field enum value causes parameter rejection
- Empty rows array (minItems:1 violated) returns error
- Extreme numeric values outside allowed range rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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