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Sampling Observations — Trailing Mean Series + Adjacent Row Changes
x402
Sampling Observations — Trailing Mean Series + Adjacent Row Changes 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 trailing moving-average series and adjacent row-to-row change analysis for up to 200 sampling observation records with sample_value and sample_weight fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes 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.
Output
Returns two analytical reports for the supplied observation rows: (1) a trailing mean series showing rolling averages of the specified field over the given window, and (2) adjacent row changes showing the difference between consecutive row values — both computed locally without external lookups or predictions.
Example use cases
Environmental sensor trend smoothing
“I have daily air quality sensor readings for 60 days across two monitoring stations — can you compute a trailing mean series with a window of 7 and also show me the day-over-day changes in the sample_value field so I can spot anomalies?”
Weekly survey response analysis
“I've got 120 weekly survey response records with scores and response weights — run a trailing mean series with a window size of 4 and adjacent row changes on sample_weight so I can see how engagement is shifting across consecutive weeks.”
Production batch quality control
“Here are 50 production batch samples with numeric quality scores and batch weights across two product groups — calculate both a rolling mean using a window of 3 and the row-to-row differences on sample_value so my QC team can track drift between consecutive batches.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-146?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a trailing moving average AND adjacent row change analysis on sampling observation data in a single $0.01 call covering up to 200 rows. It is ideal for time-series or sequential measurement data with sample weights, and when you want two complementary analytical views (smoothing + delta) without making separate API calls. Prefer alternatives if you need only one of the two reports, require grouped summary statistics, need distribution histograms, or require real-time data fetching.
Side effects
- Fewer than 1 row supplied — minItems validation error
- More than 200 rows supplied — maxItems exceeded error
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- Window size outside 2–200 range — schema validation error
- sample_value or sample_weight outside ±1,000,000,000,000 range — validation error
- Missing required fields (row_id, dataset_group, date) — required field error
- Invalid field enum value (not sample_value or sample_weight) — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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