{"uid":"cap_aq6BHZHCx4dkMcdXid2gM","slug":"save-files-analytics-two-measure-correlation-explicit-missing-value-16d1a8a0","name":"Save Files Analytics — Two-Measure Correlation + Explicit Missing-Value Fill","description":"Save files — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + 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-13-184?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"}}},"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_p6wU1ZidIDYIBIvjTkg0b","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 Pearson/rank correlation between save_kb and write_ms fields and fills missing values using zero, mean, or median strategy for up to 200 game save-file records.","exampleAgentPrompt":"I have up to 200 rows of game save-file records with save_kb and write_ms columns — can you run a two-measure correlation between those two fields and fill any missing save_kb values using the median, grouping by game_area and date?","exampleUseCases":[{"title":"Game save performance correlation study","prompt":"I've got 150 rows of game save records with fields like row_id, game_area, date, save_kb, and write_ms — please compute the correlation between save file size and write latency, and fill any missing save_kb values using the mean."},{"title":"Missing write latency imputation for game data","prompt":"My game save dataset has some null write_ms values — can you fill those missing entries using the median and also give me the correlation between save_kb and write_ms across all 80 rows?"},{"title":"Cross-area save file analytics","prompt":"I have save file data for two game areas, group-a and group-b, across October 2026 — run a two-measure correlation on save_kb and write_ms and fill any missing write_ms values with zero for my 40 rows."}],"resultDescription":"Returns two independent analytical reports: (1) a two-measure correlation report showing the statistical relationship (e.g. Pearson or Spearman coefficient) between save_kb and write_ms across submitted rows, and (2) an explicit missing-value fill report showing which rows had null values and what replacement values were applied using the chosen strategy (zero, mean, or median). No external data is fetched; all computation is local.","failureModes":["Fewer than 1 row submitted — minimum row count not met","More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, game_area, date, save_kb, or write_ms) in one or more rows","Date field does not match YYYY-MM-DD pattern — validation error","Invalid fill method enum value (must be zero, mean, or median)","Invalid field enum value (must be save_kb or write_ms)","Numeric values outside allowed range (±1,000,000,000,000)","Payment of 0.01 USDC not provided or declined — 402 response"],"whenToPreferThis":"Choose this endpoint when you have game save-file performance data (save file sizes and write latencies) and need both a correlation analysis and missing-value imputation in a single call at very low cost ($0.01). It is ideal for offline/batch analytical jobs on up to 200 rows where no live data lookup or prediction is needed. Prefer this over general-purpose analytics APIs when your data specifically involves save_kb and write_ms metrics segmented by game_area.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:37:54.968Z","isFirstParty":false,"canonicalSlug":"save-files-analytics-two-measure-correlation-explicit-missing-value-16d1a8a0"}