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Building Footprint Observations — Exact Row Deduplication + IQR Outlier Flags
x402
Building Footprint Observations — Exact Row Deduplication + IQR Outlier Flags 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).
Deduplicates exact rows and flags IQR-based outliers in building footprint observation data (footprint_m2, height_m) for up to 200 records, producing 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Building footprint observations — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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 2 independent analytical reports: (1) an exact row deduplication report identifying duplicate records across the supplied rows, and (2) an IQR outlier flagging report identifying statistically anomalous values in the selected field (footprint_m2 or height_m) — all computed locally with no external lookups.
Example use cases
Building survey data cleanup
“I have a batch of 150 building survey records with footprint_m2 and height_m columns and I suspect there are duplicate entries and outlier measurements — can you run exact deduplication and IQR outlier flagging on the footprint_m2 field and give me both reports?”
Height anomaly detection in construction dataset
“Run IQR outlier detection on the height_m field across these 80 building observation rows and also deduplicate any exact duplicate records — I need the two analytical reports so I can clean up the dataset before ingesting it.”
Real estate data quality audit
“Before I import these 200 building footprint records into our database, can you check for exact duplicate rows and flag any statistical outliers in the footprint_m2 measurements using IQR analysis? I want both quality reports back.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-16-049?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local statistical data cleaning on building footprint observation datasets — specifically when you want both exact duplicate detection and IQR-based outlier flagging in a single low-cost call ($0.01 USDC for 2 reports). Ideal for pre-ingestion data quality audits on construction, real estate, or urban survey datasets with up to 200 rows containing footprint and height measurements.
Side effects
- Empty rows array or missing required row fields (row_id, station_group, date) returns validation error
- Exceeding 200 row limit causes rejection
- Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Null values in the selected numeric field may reduce outlier detection accuracy
- Invalid field enum value (not footprint_m2 or height_m) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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