{"uid":"cap_B4lk9sadhQsstNW3_tbNS","slug":"save-files-analytics-date-category-pivot-missing-value-fill-2fe7edcf","name":"Save Files Analytics — Date×Category Pivot + Missing-Value Fill","description":"Save files — Date by category pivot + Explicit missing-value fill: Date by category pivot + 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-13-189?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_YPkvPdcFVqDvQbCVXS5Q4","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":"Pivots save-file metrics (save_kb, write_ms) by date and game_area category, with explicit missing-value imputation using zero, mean, or median fill strategies.","exampleAgentPrompt":"Pivot my game save file records by date and game_area — I have up to 50 rows with save_kb and write_ms values, some nulls — use median fill for the missing save_kb values.","exampleUseCases":[{"title":"Game area save size comparison","prompt":"I have daily save file records for two game areas — group-a and group-b — across October 2026 with some missing save_kb entries. Can you pivot the data by date and game area and fill those gaps using the median?"},{"title":"Write latency heatmap by category","prompt":"Pivot my write_ms data across dates and game areas so I can see which area had the slowest write times each day, and fill any missing cells with zero."},{"title":"QA check on sparse save records","prompt":"I've got a sparse dataset of game save records with lots of null save_kb values. Run a date-by-category pivot and fill the missing values using the mean so I can spot which game areas have incomplete coverage."}],"resultDescription":"Returns two analytical reports: (1) a date×game_area pivot table for the chosen metric field, and (2) the same dataset with explicit missing-value imputation applied using the selected fill method (zero, mean, or median). Covers up to 200 rows of supplied save file records with no external data lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Unrecognized fill method value outside zero/mean/median enum","Missing required fields (row_id, game_area, date) causes row rejection","All values null for a field makes mean/median fill undefined — may default to zero","Malformed numeric values outside allowed range rejected by schema"],"whenToPreferThis":"Choose this endpoint when you have structured game save-file records (with save_kb and write_ms columns) and need a date-by-category pivot table with controlled missing-value imputation — particularly when your dataset has up to 200 rows and you want two simultaneous analytical views (pivot + fill) for a flat $0.01 fee without needing any external data sources or live lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:37:05.682Z","isFirstParty":false,"canonicalSlug":"save-files-analytics-date-category-pivot-missing-value-fill-2fe7edcf"}