{"uid":"cap_TVjcuSYrbdytWo9J8zvNr","slug":"building-footprint-observations-numeric-row-ordering-trailing-mean-f2f08b58","name":"Building Footprint Observations — Numeric Row Ordering + Trailing Mean Series","description":"Building footprint observations — Numeric row ordering + Trailing mean series: Numeric row ordering + Trailing mean series 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-16-115?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_xrnx6FMNNVAM7NaD_q8ze","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 numeric row ordering and trailing mean series for building footprint observation records (footprint_m2, height_m) across up to 200 rows.","exampleAgentPrompt":"I have 4 building footprint records with footprint_m2 and height_m values — can you rank them by numeric row order and compute a trailing mean series for footprint_m2 using a window of 2? The records are: row-1 group-a 2026-10-01 footprint=10 height=1, row-2 group-b 2026-10-02 footprint=20 height=2, row-3 group-a 2026-10-03 footprint=15 height=3, row-4 group-b 2026-10-04 footprint=30 height=4.","exampleUseCases":[{"title":"Smooth building footprint time series","prompt":"I have monthly building footprint measurements for 12 sites — can you rank them in numeric row order and compute a trailing mean with a window of 3 for the footprint_m2 field so I can spot smoothed trends over time?"},{"title":"Analyze building height rolling average","prompt":"Run a numeric row ordering and trailing mean series on my building height data — I've got 50 rows with height_m values across two station groups, and I want a window size of 5 applied to height_m to smooth out the variation."},{"title":"Compare footprint trends across station groups","prompt":"I'm reviewing footprint_m2 observations across group-a and group-b stations over Q4 — can you apply numeric row ordering and a 4-row trailing mean to these 20 building footprint records so I can see the smoothed trend for each group?"}],"resultDescription":"Two analytical reports for the supplied building footprint dataset: (1) a numeric row ordering ranking each of the submitted records, and (2) a trailing mean series computed over the specified field (footprint_m2 or height_m) using the given window size — both derived locally from the submitted data with no external lookups.","failureModes":["Fewer than 1 row submitted returns a validation error","More than 200 rows submitted exceeds the row limit","Invalid date format (not YYYY-MM-DD) causes schema rejection","Window size smaller than 2 or larger than 200 is rejected","Non-numeric values in footprint_m2 or height_m when null is not used cause type errors","Missing required fields (row_id, station_group, date) cause schema validation failure","Payment not provided or insufficient USDC results in 402 response"],"whenToPreferThis":"Choose this endpoint when you need both numeric row ordering and a trailing mean time series applied to building footprint observation data (footprint_m2 and/or height_m) in a single call for up to 200 rows, without requiring any external data lookups or live predictions. It is cost-effective at $0.01 USDC for two analytical reports simultaneously.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:10:31.941Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-numeric-row-ordering-trailing-mean-f2f08b58"}