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Humidity Observations — Daily Sum Series & Secondary-Measure Weighted Mean
x402
Humidity Observations — Daily Sum Series & 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 2026-10-23).
Computes a daily sum series and a secondary-measure weighted mean from supplied humidity observation records (up to 200 rows) using local analytical engines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Humidity observations — Daily sum series + Secondary-measure weighted mean: Daily sum series + Secondary-measure weighted mean for supplied humidity observations records (humidity_percent, observation_count). 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 daily sum series showing the total humidity_percent (or observation_count) aggregated by date, and (2) a secondary-measure weighted mean of the selected field weighted by the companion measure — both computed locally from the supplied rows without external lookups.
Example use cases
Daily humidity trend summary
“I have 90 days of humidity sensor readings from three station groups, each with a date, humidity_percent, and observation_count. Can you produce a daily sum series and a weighted mean of humidity_percent weighted by observation_count for all of them?”
Multi-station humidity quality review
“We collected humidity_percent observations at stations A and B over the past month — about 60 rows total with observation counts per day. Run the daily sum series and the secondary-measure weighted mean on humidity_percent for me.”
Seasonal humidity aggregation report
“Here are 150 rows of daily humidity readings from our weather network for summer 2025, each with a station_group, date, humidity_percent, and observation_count. Give me the daily sum series and the weighted mean of humidity_percent weighted by observation_count.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-04-142?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of pre-collected humidity observation records and need two specific statistical outputs — a daily sum series and an observation-count-weighted mean — computed analytically without any live data fetch, forecast, or external enrichment. Ideal for batch post-processing of weather station exports or IoT sensor dumps where you already hold the raw data.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, humidity_percent, observation_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) results in parsing failure
- Null values in numeric fields may affect weighted mean accuracy
- Incorrect field enum value (not 'humidity_percent' or 'observation_count') causes schema validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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