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Wind Observations String Normalisation and Secondary-Measure Weighted Mean
x402
Wind Observations String Normalisation and Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Performs string normalisation and secondary-measure weighted mean analysis on up to 200 wind observation records (wind_speed_ms or gust_speed_ms), returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Wind observations — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied wind observations records (wind_speed_ms, gust_speed_ms). 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
Two analytical reports: (1) string normalisation results for the selected field (wind_speed_ms or gust_speed_ms) across all supplied rows, and (2) a secondary-measure weighted mean computed from the observation data, grouped by station_group and date.
Example use cases
Weather station data quality check
“I've got readings from two station groups collected over October — about 80 rows each with wind_speed_ms and gust_speed_ms. Can you normalize the strings and compute a weighted mean on the wind_speed_ms field so I can compare them?”
Gust speed weighted average for storm analysis
“I have 200 rows of wind observation data from multiple stations during a recent storm event. Please compute the secondary-measure weighted mean on the gust_speed_ms field and return both the normalisation and weighted mean reports.”
Multi-station wind summary for monthly report
“Can you take these 60 wind records from three station groups dated between 2025-01-01 and 2025-01-31, run string normalisation, and give me the weighted mean for wind_speed_ms so I can include it in our monthly weather summary?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-03-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw wind observation tabular data (up to 200 rows) and need both string normalisation and a secondary-measure weighted mean computed locally without any external lookup or prediction. It is ideal for batch meteorological data preprocessing pipelines, quality assurance on weather station readings, or generating analytical summaries for wind speed and gust data grouped by station.
Side effects
- More than 200 rows submitted — request will be rejected due to maxItems constraint
- Missing required fields (row_id, station_group, date, wind_speed_ms, gust_speed_ms) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Payment not provided or insufficient USDC causes x402 payment-required error
- Both wind_speed_ms and gust_speed_ms are null for a row, which may produce incomplete weighted mean results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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