{"uid":"cap_5AJ6oVjdgFie9ntqHDzbv","slug":"save-files-analytics-numeric-interval-filter-explicit-missing-value-e102ff8b","name":"Save Files Analytics — Numeric Interval Filter + Explicit Missing-Value Fill","description":"Save files — Numeric interval filter + Explicit missing-value fill: Numeric interval filter + 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-13-135?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"},"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_dS47bXS9-8wX_DRA5Mw90","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 save-file records by a numeric range on save_kb or write_ms, and fills missing values using zero, mean, or median imputation, returning up to 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"I have a set of game save file records with save_kb and write_ms values — some are null — and I want to filter them to only include rows where save_kb is between 0 and 100, filling any missing save_kb values using median imputation. Can you run both analytical reports on up to 200 rows and show me the results?","exampleUseCases":[{"title":"Game save size range analysis","prompt":"I've got 150 rows of game save records with save_kb and some nulls — filter them to save_kb between 5 and 500, fill the missing values with the mean, and give me the two analytical reports."},{"title":"Write speed outlier removal for game areas","prompt":"Can you take my save file data for group-a and group-b, filter write_ms to only rows between 1 and 50 milliseconds, and fill any missing write_ms values with zero? I need both reports."},{"title":"Clean save data before performance dashboard","prompt":"Before I load my game save stats into the dashboard, I need to filter save_kb between 0 and 200 and fill blanks with the median — can you run the interval filter and missing-value fill on all 200 rows?"}],"resultDescription":"Returns up to 2 analytical reports covering the filtered subset of rows (those whose selected numeric field falls within the specified minimum–maximum interval) and the imputed dataset where missing values in the chosen field have been replaced using the specified method (zero, mean, or median). Reports are computed locally with no external lookups.","failureModes":["Rows with dates not matching YYYY-MM-DD pattern will fail schema validation","Providing fewer than 1 or more than 200 rows returns an error","Specifying a minimum greater than maximum may yield zero matching rows","Null row_id or row_id exceeding 80 characters will be rejected","Invalid method or field enum values will cause a validation error","Numeric values outside ±1,000,000,000,000 are rejected"],"whenToPreferThis":"Choose this endpoint when you have game save file records (save_kb, write_ms) that need both range-based filtering and missing-value imputation in a single call. It is ideal for data cleaning pipelines targeting game telemetry or save-file analytics where you need up to 2 reports on up to 200 rows without requiring external data sources or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:37:08.976Z","isFirstParty":false,"canonicalSlug":"save-files-analytics-numeric-interval-filter-explicit-missing-value-e102ff8b"}