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Sampling Observations — Exact Row Deduplication + Trailing Mean Series
x402
Sampling Observations — Exact Row Deduplication + 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).
Deduplicates exact rows and computes trailing mean series for user-supplied sampling observation records (sample_value, sample_weight) across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Exact row deduplication + Trailing mean series: Exact row deduplication + 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 deduplicated list of rows with exact duplicates removed, and (2) a trailing mean series computed over the selected field (sample_value or sample_weight) using the specified window size, all processed locally without external lookups.
Example use cases
Clean and smooth sensor sample data
“I have 120 rows of sensor sampling observations with dates, group labels, sample values, and weights — please remove any exact duplicate rows and give me a trailing mean series for sample_value using a window of 7.”
Detect repeated records in weighted survey data
“My survey sample dataset has 80 rows with sample_value and sample_weight columns — run exact row deduplication on it and also compute a trailing mean for sample_weight with a window of 4.”
Rolling average for financial sampling observations
“I've got 200 rows of financial sampling records organized by date and dataset_group — can you deduplicate them and produce a trailing mean series on sample_value with a window of 10?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-045?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously clean exact duplicate rows AND compute a trailing mean series on sampling observation data in a single low-cost call. Ideal for structured tabular data with row_id, date, group, and numeric value/weight fields, up to 200 rows, where no external data enrichment or prediction is needed — just local analytical computation.
Side effects
- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, dataset_group, sample_value, sample_weight) — validation error
- Window size less than 2 or greater than 200 — invalid parameter error
- Date values not matching YYYY-MM-DD pattern — schema validation failure
- sample_value or sample_weight outside allowed range — validation error
- Empty rows array — minItems constraint violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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