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Humidity Observations — Weighted Mean + Keyed Dataset Comparison
x402
Humidity Observations — Weighted Mean + Keyed Dataset Comparison 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 secondary-measure weighted mean and performs a keyed dataset comparison on up to 200 rows of supplied humidity observation records.
Price / call$0.01
Success—
StatusUnknown
How this service works
Humidity observations — Secondary-measure weighted mean + Keyed dataset comparison: Secondary-measure weighted mean + Keyed dataset comparison 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 derived from the supplied humidity observation data: (1) a secondary-measure weighted mean, where humidity_percent or observation_count is averaged using the other measure as weights across the provided rows; and (2) a keyed dataset comparison that matches records from the primary and secondary datasets by their identifiers and highlights differences. All processing is performed locally with no external lookups or predictions.
Example use cases
Weighted humidity summary by station group
“I've got humidity readings from 50 sensor stations across October — each row has a station group, date, humidity_percent, and observation_count. Can you compute the observation-count-weighted mean of humidity_percent across all those rows so I know the true average accounting for how many readings each station took?”
Comparing two months of humidity data
“I have humidity observation records from two different months — same stations, same structure with row_id, station_group, date, humidity_percent, and observation_count. Can you run a keyed dataset comparison between the two to see where the readings differ?”
Quality-check humidity data across two sensor networks
“We have humidity data from two sensor networks covering the same dates and station groups, and I want to cross-check them. Each dataset has up to 150 rows with humidity_percent and observation_count. Can you run both a weighted mean on the primary network's data and a keyed comparison against the secondary network's readings?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-04-186?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected humidity observation data (up to 200 rows) and need both a weighted mean statistic and a comparative analysis between two datasets in a single paid call. It is ideal for offline batch analytical tasks on weather station humidity records where no live data fetch, prediction, or external API call is needed. Prefer this over general-purpose analytics tools when working specifically with humidity_percent and observation_count fields in the weather/environmental monitoring domain and when cost-efficiency (two reports for $0.01 USDC) matters.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, station_group, date, humidity_percent, observation_count) cause validation errors
- Date field not matching YYYY-MM-DD pattern causes schema validation failure
- Empty rows array (minItems: 1 violated) returns an error
- Null values in both humidity_percent and observation_count may produce undefined weighted mean
- Mismatched row_ids between primary and secondary datasets result in incomplete comparison
- Payment not included or insufficient USDC causes 402 rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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