{"uid":"cap_x_ZtIHLRosmstF4BXPw2j","slug":"material-libraries-weighted-mean-missing-value-fill-analytics-2d691d54","name":"Material Libraries — Weighted Mean & Missing-Value Fill Analytics","description":"Material libraries — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied material libraries records (material_count, texture_mb). 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-03-187?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","material_count","texture_mb"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"texture_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"material_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","texture_mb":1,"asset_group":"group-a","material_count":10},{"date":"2026-10-02","row_id":"row-2","texture_mb":2,"asset_group":"group-b","material_count":20},{"date":"2026-10-03","row_id":"row-3","texture_mb":3,"asset_group":"group-a","material_count":15},{"date":"2026-10-04","row_id":"row-4","texture_mb":4,"asset_group":"group-b","material_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["material_count","texture_mb"],"type":"string","default":"material_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_CCMUl88IRDrN5preWddao","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 secondary-measure weighted mean and fills missing values for material library records (material_count, texture_mb) across up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"I have material library records for two asset groups with material_count and texture_mb values — some nulls — can you fill missing values using median and compute the secondary-measure weighted mean across all rows? I have 4 rows: row-1 group-a 2026-10-01 material_count=10 texture_mb=1, row-2 group-b 2026-10-02 material_count=20 texture_mb=2, row-3 group-a 2026-10-03 material_count=null texture_mb=3, row-4 group-b 2026-10-04 material_count=30 texture_mb=4.","exampleUseCases":[{"title":"Impute nulls in texture data","prompt":"Some of my material library rows are missing texture_mb values — can you fill those gaps using the mean and then give me a weighted mean report across all 50 rows? Here's my dataset with row_id, asset_group, date, material_count, and texture_mb fields."},{"title":"Weighted mean by asset group","prompt":"I need to compute a secondary-measure weighted mean for material_count across my game asset groups, using texture_mb as the weight. I have 120 rows with some null material_count entries — please fill those with zero before running the analysis."},{"title":"Audit missing values before pipeline","prompt":"Before I push my material library data into the production pipeline, can you fill any null material_count values using the median strategy and give me two analytical reports showing the weighted mean so I can spot anomalies? I've got about 80 rows across several asset groups."}],"resultDescription":"Returns 2 analytical reports: (1) a secondary-measure weighted mean of the selected field (material_count or texture_mb) and (2) explicit missing-value fill results using the chosen method (zero, mean, or median), computed locally without external lookups, for up to 200 input rows.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format not matching YYYY-MM-DD pattern — validation error","Numeric values outside the allowed range ±1,000,000,000,000 — schema rejection","Empty rows array — minItems:1 constraint violated","Unknown field or method enum value — schema validation failure","Missing required fields (row_id, asset_group, date, material_count, texture_mb) — request rejected"],"whenToPreferThis":"Choose this endpoint when you need both weighted mean computation and missing-value imputation in a single call for material library records with material_count and texture_mb fields, especially when you want two bundled reports for $0.01 USDC. Prefer this over generic statistics APIs when your data is structured around 3D asset groups and creative pipeline metadata.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T18:57:03.629Z","isFirstParty":false,"canonicalSlug":"material-libraries-weighted-mean-missing-value-fill-analytics-2d691d54"}