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Building Footprint Observations — String Normalisation + Equal-Width Histogram
x402
Building Footprint Observations — String Normalisation + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-31).
Runs string normalisation and equal-width histogram analysis on up to 200 building footprint observation records (footprint_m2 and height_m fields).
Price / call$0.01
Success—
StatusUnknown
How this service works
Building footprint observations — String normalisation + Equal-width histogram: String normalisation + Equal-width histogram 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
Two analytical reports: (1) a string normalisation report cleaning and standardising text fields in the building footprint records, and (2) an equal-width histogram report showing bin boundaries and frequency counts for the selected numeric field (footprint_m2 or height_m), both computed locally against the supplied data.
Example use cases
Urban survey footprint distribution
“I have 120 building footprint records from an urban survey with footprint_m2 and height_m columns. Can you run string normalisation and produce a 10-bin equal-width histogram on the footprint_m2 field?”
Architect dataset height binning
“I've got 80 rows of building data from our architecture project — each has a row_id, date, station_group, footprint_m2 and height_m. Please normalise the strings and generate a 5-bin histogram on height_m.”
Real estate portfolio footprint analysis
“We have 200 building records across two station groups collected during Q4 2025. Run string normalisation and a 15-bin equal-width histogram on the footprint_m2 field so I can see how footprint sizes are distributed.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-16-031?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and equal-width histogram analysis on building footprint observation data (footprint_m2, height_m) in a single low-cost call. It is ideal for offline/local analytical processing of up to 200 rows without requiring external lookups or live data sources. Prefer it over general-purpose analytics when your data is specifically structured as building footprint observations with the expected schema fields.
Side effects
- More than 200 rows submitted — request rejected with maxItems validation error
- Missing required fields (row_id, date, footprint_m2, height_m, station_group) — schema validation error
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- bins value outside 1–30 range — schema validation error
- All values null for selected field — histogram cannot be computed
- Invalid field enum value — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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