{"uid":"cap_TzT4ksA2JKHCC3JWiV882","slug":"building-footprint-iqr-outlier-flags-two-measure-correlation-388931a2","name":"Building Footprint IQR Outlier Flags + Two-Measure Correlation","description":"Building footprint observations — IQR outlier flags + Two-measure correlation: IQR outlier flags + 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-weather-16-176?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","footprint_m2","height_m"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"height_m":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"footprint_m2":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","height_m":1,"footprint_m2":10,"station_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","height_m":2,"footprint_m2":20,"station_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","height_m":3,"footprint_m2":15,"station_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","height_m":4,"footprint_m2":30,"station_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["footprint_m2","height_m"],"type":"string","default":"footprint_m2"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_xiR7ZTUsmKwIDxsEnPXkP","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Runs IQR-based outlier detection and two-measure correlation analysis on supplied building footprint observation records (footprint_m2, height_m) for up to 200 rows.","exampleAgentPrompt":"Can you run IQR outlier detection and two-measure correlation on my building footprint observations? I have 4 rows: row-1 on 2026-10-01 in group-a with footprint_m2=10 and height_m=1, row-2 on 2026-10-02 in group-b with footprint_m2=20 and height_m=2, row-3 on 2026-10-03 in group-a with footprint_m2=15 and height_m=3, row-4 on 2026-10-04 in group-b with footprint_m2=30 and height_m=4 — analyze the footprint_m2 field.","exampleUseCases":[{"title":"Flag outlier buildings in survey batch","prompt":"I have a batch of 50 building survey records with footprint and height measurements — can you flag any IQR outliers and show me the correlation between footprint_m2 and height_m across all of them?"},{"title":"Quality check urban building dataset","prompt":"Run an IQR outlier check and two-measure correlation on these building footprint observations from my urban planning dataset — I want to catch any anomalous footprint_m2 values before I use this data in a report."},{"title":"Detect skewed heights in construction records","prompt":"I've got construction records with height_m and footprint_m2 for about 80 buildings grouped into two districts — can you detect IQR outliers in height_m and compute the correlation between those two measures?"}],"resultDescription":"Returns two analytical reports per call: (1) IQR outlier flags for each row indicating whether the selected measure (footprint_m2 or height_m) falls outside the interquartile range bounds, and (2) a two-measure correlation result between footprint_m2 and height_m across all supplied rows. Results are computed locally on supplied data only, with no external lookups.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, date, footprint_m2, height_m, station_group) — schema validation failure","Date field not matching YYYY-MM-DD pattern — pattern validation error","Invalid field enum value (not footprint_m2 or height_m) — enum validation error","All values null for selected measure — IQR computation not possible","Payment not processed — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 building footprint observation records with footprint_m2 and height_m fields and need both IQR-based outlier detection and cross-measure correlation in a single paid call. It is purpose-built for building measurement data and delivers two reports for $0.01 USDC. Prefer it over generic statistics APIs when your data is already structured in the expected schema and you need fast, local computation with no external data dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:50:36.808Z","isFirstParty":false,"canonicalSlug":"building-footprint-iqr-outlier-flags-two-measure-correlation-388931a2"}