{"uid":"cap_3cRTd_1CeMXhLWUZ4O5Ni","slug":"scene-geometry-weighted-mean-with-missing-value-fill-b92c846a","name":"Scene Geometry Weighted Mean with Missing-Value Fill","description":"Scene geometry — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied scene geometry records (object_count, triangle_count). 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-creative-05-187?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","object_count","triangle_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"asset_group":{"type":"string","default":"","maxLength":80},"object_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"triangle_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","asset_group":"group-a","object_count":10,"triangle_count":1},{"date":"2026-10-02","row_id":"row-2","asset_group":"group-b","object_count":20,"triangle_count":2},{"date":"2026-10-03","row_id":"row-3","asset_group":"group-a","object_count":15,"triangle_count":3},{"date":"2026-10-04","row_id":"row-4","asset_group":"group-b","object_count":30,"triangle_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["object_count","triangle_count"],"type":"string","default":"object_count"},"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_YM_xUDvrCfKh3cyR26mfv","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 a secondary-measure weighted mean for scene geometry data (object_count, triangle_count) and fills missing values using a chosen fill method, returning 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you compute the secondary-measure weighted mean for my scene geometry records and fill any missing object_count values using median imputation? I have about 50 rows across two asset groups — group-a and group-b — dated from 2026-10-01 to 2026-10-31.","exampleUseCases":[{"title":"3D asset pipeline geometry audit","prompt":"I have 120 scene geometry records from our rendering pipeline with some missing triangle_count values — can you fill those nulls using the mean method and then compute a weighted mean of triangle_count weighted by object_count for each asset group?"},{"title":"Game level object count analysis","prompt":"I need to analyze object_count across our game level geometry records for October 2026 — fill any missing object_count values with zero and give me the secondary-measure weighted mean grouped by asset group across up to 80 rows."},{"title":"Missing data imputation for geometry metrics","prompt":"Some of my scene geometry rows have null values in object_count and triangle_count — can you use median fill to patch those gaps and then compute the weighted mean of object_count across all 40 rows split by asset group?"}],"resultDescription":"Returns 2 analytical reports containing: (1) a secondary-measure weighted mean of the specified field (object_count or triangle_count) across the supplied rows, and (2) the dataset with missing values filled using the chosen method (zero, mean, or median). Results are scoped to the submitted rows only — no external data is fetched.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, date, asset_group) cause validation errors","Invalid date format (not YYYY-MM-DD) fails pattern validation","All values in target field are null — weighted mean may be undefined","Invalid enum value for field or method parameters returns schema error","Payment of 0.01 USDC not completed causes 402 rejection"],"whenToPreferThis":"Choose this endpoint when you need both weighted-mean aggregation and missing-value imputation for 3D scene geometry data (object_count, triangle_count) in a single call, especially when working with up to 200 rows and needing two analytical reports at low cost. Prefer this over general analytics tools when your data is specifically structured as scene geometry records with asset_group and date dimensions, and you want deterministic local computation with no external lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T18:57:01.302Z","isFirstParty":false,"canonicalSlug":"scene-geometry-weighted-mean-with-missing-value-fill-b92c846a"}