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Forecast Verification Inputs — Daily Sum Series + Explicit Missing-Value Fill
x402
Forecast Verification Inputs — Daily Sum Series + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Computes a daily sum series and fills missing values (zero, mean, or median) for forecast vs. observed value records, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — Daily sum series + Explicit missing-value fill: Daily sum series + Explicit missing-value fill for supplied forecast verification inputs records (forecast_value, observed_value). 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 independent analytical reports: (1) a daily sum series aggregated from the supplied forecast_value and observed_value rows, and (2) an explicit missing-value fill result for the chosen field (forecast_value or observed_value) using the specified method (zero, mean, or median). Reports cover up to 200 input rows grouped by date and station_group.
Example use cases
Weather station forecast accuracy audit
“I have daily forecast and observed precipitation records for station groups north-a and north-b covering the past 6 months, with some nulls in the observed_value column — run the daily sum series and fill those missing observed values using the mean, up to 200 rows.”
Null imputation before model retraining
“Before I retrain my forecasting model, I need to fill all missing forecast_value entries in my 80-row verification dataset using zero imputation and get the daily sum series so I can spot any anomalies by date.”
Station group daily aggregation report
“Can you take these 120 rows of forecast vs. actual temperature readings split across group-east and group-west, generate the daily sum series, and fill any gaps in forecast_value with the median — I need both reports back.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-145?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular forecast vs. observed value records (up to 200 rows) that need both a daily sum aggregation and explicit missing-value imputation in a single call at low cost ($0.01 USDC). It is particularly suited for weather or time-series verification workflows where null handling and daily aggregation are needed together without an external data lookup or live prediction service.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (not YYYY-MM-DD) causes validation error
- Missing required fields (row_id, date, forecast_value, observed_value) cause schema rejection
- Values outside ±1,000,000,000,000 range rejected
- Invalid enum for method or field parameter causes error
- Empty rows array rejected (minItems: 1)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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