{"uid":"cap_XNQzEC-xSpYXlbKTMQ2ah","slug":"building-footprint-observations-numeric-interval-filter-trailing-mean-58f152cd","name":"Building Footprint Observations — Numeric Interval Filter + Trailing Mean Series","description":"Building footprint observations — Numeric interval filter + Trailing mean series: Numeric interval filter + 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-16-126?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},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_tEKgoD4jOwLUzgRZeMKDm","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":"Filters building footprint observation records by a numeric interval and computes a trailing mean series for footprint_m2 or height_m fields, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 150 building footprint observations with footprint_m2 and height_m columns — can you filter the records where footprint_m2 falls between 50 and 500, then compute a trailing mean series with a window of 5 for the footprint_m2 field?","exampleUseCases":[{"title":"Urban density analysis for city planners","prompt":"I have 200 rows of building footprint observations from downtown — filter them to only include buildings where footprint_m2 is between 100 and 800, and give me a trailing mean series with a window of 10 for footprint_m2 so I can see size trends over time."},{"title":"Height compliance check with rolling average","prompt":"Here are 80 building records from our site survey — filter to height_m values between 5 and 30 meters and compute a trailing mean series with a window of 3 for height_m so I can spot anomalies in the rolling average."},{"title":"Portfolio footprint trend reporting","prompt":"I need two analytical reports on these 120 building footprint observations: filter footprint_m2 values between 200 and 1000, and run a trailing mean series with window 7 on footprint_m2 grouped by station_group."}],"resultDescription":"Returns two analytical reports: (1) records from the input dataset where the selected field (footprint_m2 or height_m) falls within the specified numeric interval [minimum, maximum], and (2) a trailing mean series computed over the selected field using the specified window size. Both reports cover up to 200 input rows and are computed locally without external data lookups.","failureModes":["Fewer than 1 row supplied — returns validation error","More than 200 rows supplied — rejected with maxItems error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Minimum value greater than maximum value — may return empty filtered result with no error","Window size larger than number of rows — trailing mean series may return nulls or partial results","Null values in target field — nulls may propagate into mean calculations","Missing required row fields (row_id, station_group, date) — schema validation error"],"whenToPreferThis":"Choose this endpoint when you have building footprint or height observation records and need both a numeric range filter and a rolling/trailing mean series in a single call. It is well-suited for small-to-medium datasets (up to 200 rows) where you want two bundled analytical outputs without building custom code. Prefer it over general-purpose data tools when your data specifically involves footprint_m2 and height_m columns and you need a cost-effective ($0.01 USDC for both reports) batch computation.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T19:11:12.441Z","isFirstParty":false,"canonicalSlug":"building-footprint-observations-numeric-interval-filter-trailing-mean-58f152cd"}