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Elevation Samples — Trailing Mean Series + Date by Category Pivot
x402
Elevation Samples — Trailing Mean Series + Date by Category Pivot 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 a trailing mean time series and a date-by-category pivot table from supplied elevation sample records (elevation_m, sample_weight) for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Elevation samples — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot for supplied elevation samples records (elevation_m, 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 trailing mean time series computed over the specified numeric field (elevation_m or sample_weight) using the given window size, and (2) a date-by-category pivot table cross-tabulating values by date and station_group. Both reports are derived entirely from the supplied input rows with no external data lookups.
Example use cases
Smoothing elevation sensor readings over time
“I've got a series of 50 elevation readings from two sensor stations — alpine-north and alpine-south — taken daily from 2026-09-01 to 2026-10-20. Can you give me a trailing mean series with a window of 5 on elevation_m and also pivot the data by date and station group?”
Analyzing weighted survey samples by region
“Here are 120 elevation survey records from field teams across three site groups — site-east, site-west, and site-central — each with a date, elevation in meters, and a sample weight. Run a trailing mean series with window 3 on the sample_weight field and produce a date-by-category pivot table for the full dataset.”
Comparing elevation trends across monitoring stations
“I have 80 rows of elevation monitoring data across four station groups spanning 2025-01-01 to 2025-03-31, each tagged with a row ID, date, elevation_m, and sample_weight. Please compute a trailing mean with window 7 on elevation_m and also give me a cross-tabulation of elevations by date and station group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-13-152?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have elevation or sample-weight time-series data organized by station group and date and need both a rolling/trailing mean smoothing report and a date-by-category pivot summary in a single call. It is ideal for offline analytical batch processing of up to 200 rows without requiring external data sources, live lookups, or predictions. Not suitable for real-time elevation lookups, geolocation queries, or datasets exceeding 200 rows.
Side effects
- Fewer than 1 or more than 200 rows submitted — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Window size smaller than 2 or larger than 200 — rejected input
- Missing required fields (row_id, station_group, date, elevation_m, sample_weight) — schema error
- Non-numeric values in elevation_m or sample_weight fields — type error
- Payment of 0.01 USDC not provided or rejected — 402 Payment Required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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