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Building Footprint Observations — Daily Sum + Secondary-Measure Weighted Mean
x402
Building Footprint Observations — Daily Sum + 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 2026-10-25).
Computes a daily sum time series and a secondary-measure weighted mean for up to 200 supplied building footprint observation records (footprint_m2, height_m).
Price / call$0.01
Success—
StatusUnknown
How this service works
Building footprint observations — Daily sum series + Secondary-measure weighted mean: Daily sum series + Secondary-measure weighted mean for supplied building footprint observations records (footprint_m2, height_m). 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 for the supplied building footprint records: (1) a daily sum time series showing totals of the selected field (footprint_m2 or height_m) per day, and (2) a secondary-measure weighted mean using the other field as the weighting variable. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Daily footprint totals for urban planning
“I have 120 building observation records with dates, footprint sizes in square meters, and heights in meters across several station groups — can you generate a daily sum time series and a weighted mean report for the footprint_m2 field so I can see how total covered area varies day by day?”
Height-weighted analysis for construction dataset
“I've got a dataset of 80 building records with dates, row IDs, station groups, footprint areas, and heights — please run a daily sum series and a height_m weighted mean on these so I can understand the distribution of building heights weighted by footprint size.”
Station group aggregation for real estate portfolio
“Can you take my 200 building footprint observations — each with a date, station group, footprint_m2, and height_m — and compute both the daily sum series and the secondary-measure weighted mean for the footprint_m2 field across all station groups?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-16-142?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured building footprint observation records (with footprint_m2 and height_m fields) and need both a daily aggregated sum time series AND a weighted mean statistic in a single API call. It is ideal for offline/batch analytical workflows where no live data lookup or external enrichment is needed, and cost efficiency matters ($0.01 for two reports on up to 200 rows).
Side effects
- More than 200 rows submitted — request rejected at input validation
- Missing required fields (row_id, station_group, date, footprint_m2, height_m) — validation error
- Invalid date format (must be YYYY-MM-DD) — pattern validation failure
- Numeric values out of allowed range (±1,000,000,000,000) — schema rejection
- Empty rows array — minItems:1 violation
- Invalid field enum value (must be footprint_m2 or height_m) — enum validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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