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Temperature Observations — Weighted Mean & Date-by-Category Pivot
x402
Temperature Observations — Weighted Mean & 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 2026-11-03).
Computes a secondary-measure weighted mean and a date-by-category pivot table for supplied temperature observation records in a single paid call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Temperature observations — Secondary-measure weighted mean + Date by category pivot: Secondary-measure weighted mean + Date by category pivot for supplied temperature observations records (temperature_c, 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 secondary-measure weighted mean of temperature_c (or observation_count) using the other numeric column as the weight, and (2) a pivot table with dates as rows and station_group categories as columns showing aggregated temperature values — all computed locally from the supplied data, up to 200 rows.
Example use cases
Monthly station temperature summary
“I have daily temperature readings from three weather station groups across October — each row has a date, station group, temperature in Celsius, and how many observations were taken that day. Can you compute the observation-count weighted mean temperature and give me a date-by-station-group pivot for the whole month?”
Climate data QA pivot report
“I need to cross-check my temperature dataset — it has about 150 rows with station_group, date, temperature_c, and observation_count. Please run both the weighted mean report and the date-by-category pivot so I can spot any anomalies across groups.”
Multi-station aggregation for dashboard
“We're building a weather dashboard and I want to summarize raw temperature observations — about 80 rows with columns row_id, station_group, date, temperature_c, and observation_count. Can you give me the observation-count weighted average temperature and a pivot table of temperatures by date and station group?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-01-185?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-collected temperature observation records (up to 200 rows) and need both a weighted mean aggregation and a date-by-category pivot in a single low-cost call. It is ideal for offline/batch analytical tasks on weather station data where no live data lookup, prediction, or external data enrichment is needed — just local computation on your supplied rows.
Side effects
- Missing required fields (row_id, date, station_group, temperature_c, observation_count) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Input array exceeding 200 rows is rejected with a size-limit error
- Null values in temperature_c or observation_count may affect weighted mean accuracy
- Invalid field enum value (not 'temperature_c' or 'observation_count') causes a schema error
- Payment failure (insufficient USDC balance) prevents processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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