{"uid":"cap_nTvSm9f5x4JracbnoR3Nf","slug":"building-footprint-observations-two-measure-correlation-explicit-a7925598","name":"Building Footprint Observations — Two-Measure Correlation + Explicit Missing-Value Fill","description":"Building footprint observations — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill 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-16-184?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_MC55QtqPcXSzEoVjuvQh8","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":"Computes pairwise correlation between footprint_m2 and height_m, and fills missing values in a chosen field using zero, mean, or median imputation, across up to 200 building observation rows.","exampleAgentPrompt":"I have 150 building observation records with footprint_m2 and height_m fields — some height_m values are missing. Can you compute the correlation between footprint and height, and fill the missing height_m values using median imputation?","exampleUseCases":[{"title":"Impute missing building heights for dataset","prompt":"I've got a dataset of 80 building records — some height_m values are null. Can you fill in the missing height_m values using median imputation and also tell me how footprint_m2 and height_m correlate across the dataset?"},{"title":"Correlation check for urban planning analysis","prompt":"I'm analyzing buildings across two station groups and need to know if footprint area and height are correlated. I have 120 rows with footprint_m2 and height_m — can you run the two-measure correlation report for me?"},{"title":"Zero-fill missing footprint values before export","prompt":"Before I export my building dataset, I need to replace any missing footprint_m2 values with zero. I have about 60 rows across a few groups — can you fill those nulls and also give me the correlation between footprint and height?"}],"resultDescription":"Returns two analytical reports for the submitted building footprint observation rows: (1) a pairwise correlation analysis between footprint_m2 and height_m across the supplied records, and (2) a missing-value-filled version of the specified field (footprint_m2 or height_m) using the chosen imputation strategy (zero, mean, or median). Results are computed locally with no external lookups.","failureModes":["Fewer than 1 row submitted — violates minItems constraint","Row missing required fields (row_id, date, footprint_m2, height_m, station_group) — schema validation error","Date field not in YYYY-MM-DD format — pattern validation failure","More than 200 rows submitted — exceeds maxItems limit","Invalid enum value for method or field — rejected by schema","All values in the target field are null — imputation may produce degenerate results","Correlation undefined if one variable has zero variance — may return NaN or error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 building observation records with footprint_m2 and height_m columns and need both a correlation analysis between those two measures and missing-value imputation in a single call. Ideal for offline/batch data preparation workflows where no live data lookup or external enrichment is needed. Prefer this over general-purpose analytics when the specific combination of two-measure correlation plus explicit missing-value fill on building footprint data is required at minimal cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:34:14.905Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-two-measure-correlation-explicit-a7925598"}