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Building Footprint Observations — Numeric Interval Filter + Two-Measure Correlation
x402
Building Footprint Observations — Numeric Interval Filter + Two-Measure Correlation 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).
Filters building footprint observation rows by a numeric interval and computes a two-measure correlation report between footprint_m2 and height_m for up to 200 supplied rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Building footprint observations — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation 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: (1) a numeric interval filter report listing which rows fall within the specified min/max range for the chosen field (footprint_m2 or height_m), and (2) a two-measure correlation report quantifying the statistical relationship between footprint_m2 and height_m across the supplied rows. Up to 200 input rows are supported per call.
Example use cases
Urban density correlation study
“I've got 150 building records with footprint area and height measurements. Filter the ones where height_m is between 10 and 80 meters and tell me how correlated height_m is with footprint_m2 across the whole set.”
Filtering oversized footprints for compliance review
“Run an interval filter on my building footprint data — I only want rows where footprint_m2 falls between 200 and 500 — and also give me a two-measure correlation between footprint_m2 and height_m for those buildings.”
Real estate portfolio measurement analysis
“Here are my building observation records for station group 'portfolio-east' across October 2026. Can you filter to buildings with footprint_m2 between 0 and 150 and compute the correlation between building footprint and height?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-16-131?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 building footprint observation records with both footprint_m2 and height_m fields and need both a numeric range filter and a two-measure correlation in a single call. It is ideal for offline/batch analytical work on supplied data rather than live lookups or predictions. Prefer this over general-purpose statistics tools when you specifically need interval filtering paired with a correlation report on building measurement data within a single $0.01 call.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, station_group, footprint_m2, height_m) cause validation errors
- Date strings not matching YYYY-MM-DD pattern will fail schema validation
- Minimum value greater than maximum value may produce empty filter results
- Null values in footprint_m2 or height_m may reduce correlation sample size or cause computation errors
- Invalid field enum value (not footprint_m2 or height_m) will fail validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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