{"uid":"cap_rY78vgFbOGWGrZ2FwT_Ck","slug":"dataset-storage-analytics-date-category-pivot-with-missing-value-fill-3f162263","name":"Dataset Storage Analytics — Date×Category Pivot with Missing-Value Fill","description":"Dataset storage — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied dataset storage records (used_mb, row_count). 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-analytics-18-189?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","used_mb","row_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"used_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"row_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","used_mb":10,"row_count":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","used_mb":20,"row_count":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","used_mb":15,"row_count":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","used_mb":30,"row_count":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["used_mb","row_count"],"type":"string","default":"used_mb"},"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_Y1sWht_qe_xU236clmDH7","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 dataset storage records (used_mb or row_count) by date and category, filling missing values via zero, mean, or median, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Pivot my dataset storage records by date and dataset_group for the used_mb metric — fill any missing values using median — here are my rows: group-a had 10 MB on 2026-10-01 and 15 MB on 2026-10-03, group-b had 20 MB on 2026-10-02 and 30 MB on 2026-10-04.","exampleUseCases":[{"title":"Storage usage trend by team","prompt":"I have 120 rows of dataset storage logs with columns for date, dataset_group, and used_mb. Can you pivot them into a date-by-group table and fill any missing cells with the median so I can see which team is using the most storage each day?"},{"title":"Row count cross-tab with zero-fill","prompt":"Take my dataset records — up to 180 rows — and create a pivot table of row_count grouped by date and dataset_group. Fill any missing date-group combinations with zero rather than leaving blanks."},{"title":"Missing-value imputation before reporting","prompt":"My storage dataset has gaps where some groups didn't log data on certain dates. Pivot the used_mb values by date and category, using mean imputation for the missing cells, so I get a clean matrix across all 90 rows."}],"resultDescription":"Returns two analytical reports: (1) a date-by-category pivot table of the selected metric (used_mb or row_count) with missing values explicitly filled using the chosen method (zero, mean, or median), and (2) a supplementary summary report — both computed locally from the supplied rows with no external data lookup.","failureModes":["Fewer than 1 row supplied returns a validation error","More than 200 rows submitted exceeds the row limit","Invalid date format (not YYYY-MM-DD) causes schema rejection","Unknown fill method outside zero/mean/median is rejected","Unknown field outside used_mb/row_count is rejected","Null-only columns may produce degenerate mean/median fill results"],"whenToPreferThis":"Choose this endpoint when you have raw dataset storage records (with used_mb or row_count fields) that need to be reshaped into a date-by-category pivot table with explicit missing-value handling, all within a single low-cost call. It is ideal for offline/batch analytical reshaping of up to 200 rows when no live data lookup, prediction, or external enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:41.442Z","isFirstParty":false,"canonicalSlug":"dataset-storage-analytics-date-category-pivot-with-missing-value-fill-3f162263"}