Sampling Observations — Adjacent Row Changes + Explicit 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 2026-10-15).
Computes adjacent row changes and fills missing values (zero, mean, or median) for up to 200 rows of weighted sampling observation data, returning 2 analytical reports.
Sampling observations — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied sampling observations records (sample_value, sample_weight). 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 analytical reports: (1) adjacent row changes showing the delta between consecutive rows for the selected field, and (2) missing-value fill results where null entries are replaced using the chosen method (zero, mean, or median). Both reports are computed locally from the supplied data with no external lookups.
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-162?utm_source=zero.xyzChoose this endpoint when you have up to 200 rows of weighted sampling observations and need both adjacent row-change detection and missing-value imputation in a single call. Ideal for survey data, sensor readings, or longitudinal studies where nulls need filling and sequential deltas matter. Prefer this over general-purpose analytics tools when you want a low-cost ($0.01), self-contained computation that does not require any external data or live lookups.
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
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