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Wind Observations — Exact Row Deduplication + Secondary-Measure Weighted Mean
x402
Wind Observations — Exact Row Deduplication + 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 2026-10-29).
Deduplicates wind observation records exactly and computes a secondary-measure weighted mean across up to 200 rows of wind speed and gust speed data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Wind observations — Exact row deduplication + Secondary-measure weighted mean: Exact row deduplication + 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
Returns two analytical reports: (1) the result of exact row deduplication applied to the submitted wind observation records, and (2) a secondary-measure weighted mean computed over the selected field (wind_speed_ms or gust_speed_ms), both processed locally against up to 200 supplied rows.
Example use cases
Cleaning duplicate weather station data
“I've collected wind readings from multiple stations and I suspect there are duplicate rows — can you deduplicate them exactly and give me the weighted mean of wind_speed_ms across all the records? I'll send you about 120 rows with row_id, station_group, date, wind_speed_ms, and gust_speed_ms.”
Weighted mean gust speed by station group
“I need to compute the weighted mean of gust_speed_ms from my wind observation dataset — it has 80 rows with station groups and daily dates. Can you deduplicate the data first and then give me the weighted mean report for gust_speed_ms?”
QA pass on wind sensor logs before reporting
“Before I submit my wind sensor logs to the report, can you run an exact deduplication pass on my 200 observation rows and then compute the weighted mean for wind_speed_ms so I can verify the data looks clean and consistent?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-03-051?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw wind observation records (with wind speed and gust speed) that may contain exact duplicate rows and you need both a deduplicated dataset and a weighted mean of one of the two measures. Ideal for data cleaning and QA pipelines for meteorological or environmental sensor data, especially when working in batches of up to 200 rows with no need for live lookups or external data enrichment.
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, station_group, date, wind_speed_ms, gust_speed_ms) causes validation error
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Null values for both wind_speed_ms and gust_speed_ms may affect weighted mean computation
- Empty rows array rejected by minItems:1 constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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