{"uid":"cap_2MAFNSeWpQOzDSg5tz4cP","slug":"save-files-analysis-trailing-mean-series-explicit-missing-value-fill-0ba77e4f","name":"Save Files Analysis — Trailing Mean Series + Explicit Missing-Value Fill","description":"Save files — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied save files records (save_kb, write_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-13-154?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","save_kb","write_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"save_kb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"write_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"game_area":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","save_kb":10,"write_ms":1,"game_area":"group-a"},{"date":"2026-10-02","row_id":"row-2","save_kb":20,"write_ms":2,"game_area":"group-b"},{"date":"2026-10-03","row_id":"row-3","save_kb":15,"write_ms":3,"game_area":"group-a"},{"date":"2026-10-04","row_id":"row-4","save_kb":30,"write_ms":4,"game_area":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["save_kb","write_ms"],"type":"string","default":"save_kb"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"},"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_qdchgpwJWKPrNy50zXYwS","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 trailing moving-average series and fills missing values (via zero, mean, or median) for save file metrics (save_kb, write_ms) across up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"I have 50 rows of daily save file data with save_kb and write_ms values — some are null. Can you compute a trailing mean series with a window of 5 for save_kb and fill in the missing values using median imputation?","exampleUseCases":[{"title":"Smoothing noisy save-size data","prompt":"I've got 120 rows of daily game save file records with save_kb measurements, but there are gaps where the value is null. Can you fill the missing save_kb values using mean imputation and then compute a trailing mean series with a window of 7 so I can see the smoothed trend?"},{"title":"Write latency trend analysis","prompt":"Here are 80 rows of game area save telemetry including write_ms timestamps. Some write_ms entries are missing — fill them with zeros and give me a trailing mean series over a window of 3 so I can spot performance regressions by game area."},{"title":"Pre-processing save data for reporting","prompt":"I need to clean up this batch of 200 save file records before sending them to my reporting dashboard — fill any null save_kb values using median and compute a rolling 10-day trailing mean so the chart lines don't jump around."}],"resultDescription":"Returns two analytical reports: (1) a trailing mean series for the chosen field (save_kb or write_ms) computed over the specified window, and (2) the same dataset with missing values explicitly filled using the chosen method (zero, mean, or median), both applied to the supplied rows.","failureModes":["Fewer than 1 or more than 200 rows supplied returns a validation error","Invalid date format (not YYYY-MM-DD) causes row rejection","Window size smaller than 2 or larger than 200 is rejected","Unknown fill method (not zero/mean/median) causes a schema error","Rows missing required fields (row_id, game_area, date) are rejected","Numeric values outside ±1,000,000,000,000 bounds cause validation failure"],"whenToPreferThis":"Choose this endpoint when you have tabular save-file telemetry (save_kb or write_ms) that needs both missing-value imputation and trailing moving-average smoothing in a single call, with no external data sources required. It is ideal for pre-processing game analytics data before visualization or downstream ML pipelines, especially when rows contain nulls and you want a clean time-series output. Prefer alternatives if you need live lookups, forecasting, or metrics beyond save_kb/write_ms.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-06T00:34:22.448Z","isFirstParty":false,"canonicalSlug":"save-files-analysis-trailing-mean-series-explicit-missing-value-fill-0ba77e4f"}