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Sampling Observations — Numeric Interval Filter + Trailing Mean Series
x402
Sampling Observations — Numeric Interval Filter + Trailing Mean Series 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).
Filters sampling observation rows by a numeric interval and computes a trailing mean series over user-supplied sample data, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Numeric interval filter + Trailing mean series: Numeric interval filter + Trailing mean series 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: (1) a numeric interval-filtered subset of the supplied sampling observation rows where the target field falls within the specified minimum and maximum bounds, and (2) a trailing mean series computed over the chosen field (sample_value or sample_weight) using the specified window size. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Quality control sample range screening
“I have 150 product measurement samples with dates, values, and weights — filter them so only records where sample_value falls between 5 and 95 make it through, then give me a trailing mean series with a window of 5 over sample_value so I can spot trends in my batch data.”
Survey response rolling average analysis
“Here are 80 rows of survey response observations with sample_value scores and sample_weight fields — I need to filter out any responses outside the range 10 to 200, and then calculate a trailing mean with window size 4 over sample_value to see how the average evolves across dates.”
Environmental sensor data smoothing
“I've collected 120 sensor readings across two site groups, each with a sample_value and sample_weight — please filter readings between -50 and 500, then compute a rolling mean series using a window of 7 over sample_weight so I can smooth out noise in the weighted measurements.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-126?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of sampling observation data (with sample_value and sample_weight fields) and need both a numeric interval filter and a trailing mean series computed in a single paid call for $0.01 USDC. It is ideal for offline/batch analytical workflows where no live data lookup, prediction, or external action is needed — just local statistical computation on supplied data.
Side effects
- Input array is empty or missing required fields (row_id, date, sample_value, sample_weight, dataset_group) — validation error
- More than 200 rows supplied — rejected with maxItems error
- Window size larger than number of input rows — may produce empty or partial trailing mean series
- Minimum greater than maximum — interval filter returns no rows
- Non-conforming date format (not YYYY-MM-DD) — pattern validation failure
- Null values in sample_value or sample_weight may be excluded from computations silently
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer | |
| maximum | number | |
| minimum | number |
Tags
x402
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