{"uid":"cap_N0r2mQSycGhZKHHZ0O3k0","slug":"physics-scenes-data-cleaner-string-normalisation-missing-value-fill-c4949a77","name":"Physics Scenes Data Cleaner — String Normalisation + Missing Value Fill","description":"Physics scenes — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied physics scenes records (body_count, step_ms). 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-game-08-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","body_count","step_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"step_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"game_area":{"type":"string","default":"","maxLength":80},"body_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","step_ms":1,"game_area":"group-a","body_count":10},{"date":"2026-10-02","row_id":"row-2","step_ms":2,"game_area":"group-b","body_count":20},{"date":"2026-10-03","row_id":"row-3","step_ms":3,"game_area":"group-a","body_count":15},{"date":"2026-10-04","row_id":"row-4","step_ms":4,"game_area":"group-b","body_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["body_count","step_ms"],"type":"string","default":"body_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_zN-Y99Jo9t83Dg2iexnr_","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":"Normalises strings and fills missing values in physics simulation scene records (body_count, step_ms) across up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Can you clean my physics scene data — normalise the strings and fill missing body_count values using median imputation? I have 4 rows: row-1 on 2026-10-01 in group-a with body_count 10 and step_ms 1, row-2 on 2026-10-02 in group-b with body_count null and step_ms 2, row-3 on 2026-10-03 in group-a with body_count 15 and step_ms null, row-4 on 2026-10-04 in group-b with body_count 30 and step_ms 4.","exampleUseCases":[{"title":"Impute missing body counts in simulation data","prompt":"I have 50 physics scene records exported from my game engine and several body_count fields are null — can you fill them using median imputation and normalise the string fields like game_area at the same time?"},{"title":"Zero-fill missing step timing before pipeline ingest","prompt":"Before I push my physics scene logs into our analytics pipeline I need to zero-fill any missing step_ms values and normalise all the strings — can you run that cleaning on my 120 rows and give me the two reports?"},{"title":"Audit and fix game area labels with mean fill","prompt":"My game physics dataset has inconsistent game_area labels and some null body_count entries — please normalise the strings and fill those missing body_count values using the mean, for all 80 rows I'm sending."}],"resultDescription":"Two analytical reports covering (1) string normalisation results for the supplied physics scene records and (2) explicit missing-value fill results for the chosen field (body_count or step_ms) using the selected method (zero, mean, or median), applied across up to 200 input rows. No external lookups or predictions are included.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) — schema validation error","Unknown fill method value outside zero/mean/median enum — rejected","Missing required fields (row_id, game_area, date, body_count, step_ms) — validation error","Numeric values outside allowed range (±1,000,000,000,000) — schema error"],"whenToPreferThis":"Choose this endpoint when you have raw physics simulation or game scene records that contain dirty string labels or null numeric fields (body_count or step_ms) and need both string normalisation and missing-value imputation delivered together as two reports in a single call, without needing live data lookups or predictive modelling. It is especially suited for small-to-medium batches (up to 200 rows) at very low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:33:16.780Z","isFirstParty":false,"canonicalSlug":"physics-scenes-data-cleaner-string-normalisation-missing-value-fill-c4949a77"}