{"uid":"cap_tJq6bpOVH1nqFu6MeybBH","slug":"data-reconciliation-date-category-pivot-missing-value-fill-7b8879bf","name":"Data Reconciliation — Date×Category Pivot + Missing-Value Fill","description":"Data reconciliation — Date by category pivot + Explicit missing-value fill: Date by category pivot + Explicit missing-value fill for supplied data reconciliation records (source_total, target_total). 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-11-189?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_total","target_total"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_total":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"target_total":{"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","source_total":10,"target_total":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_total":20,"target_total":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_total":15,"target_total":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_total":30,"target_total":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["source_total","target_total"],"type":"string","default":"source_total"},"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_jiiaej9Vfuw5EB57oeiK2","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 reconciliation rows by date and dataset group, then fills missing source_total or target_total values using zero, mean, or median imputation — returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 4 reconciliation rows with source and target totals across two groups (group-a and group-b) on dates 2026-10-01 through 2026-10-04 — can you pivot them by date and category and fill any missing source_total values using median imputation?","exampleUseCases":[{"title":"Monthly finance reconciliation pivot","prompt":"I've got 150 reconciliation records with source_total and target_total across three dataset groups and daily dates for October — pivot them by date and group, and fill any missing source_total values using the median so I can spot discrepancies."},{"title":"Null-safe target total comparison","prompt":"My target_total column has some nulls in this reconciliation dataset of 80 rows across two groups. Fill the missing target_total values with the group mean and give me the date-by-category pivot so I can review the comparison cleanly."},{"title":"Data quality check before reporting","prompt":"Before I send this reconciliation file to finance, can you pivot the 60 rows by date and dataset group and replace any missing source_total entries with zero so the pivot is complete with no gaps?"}],"resultDescription":"Two analytical reports: (1) a date-by-category pivot table of the selected field (source_total or target_total) across all dataset groups and dates, and (2) a missing-value fill report showing which cells were imputed and what values were used, based on the chosen method (zero, mean, or median). Up to 200 input rows supported.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, dataset_group, source_total, target_total) on any row — validation error","Date strings not matching YYYY-MM-DD format — pattern validation failure","Numeric values outside ±1,000,000,000,000 range — schema rejection","Empty rows array (minItems: 1 not met) — validation error","Invalid enum value for field or method — schema rejection"],"whenToPreferThis":"Choose this endpoint when you need to reshape reconciliation data into a date-by-category pivot AND handle missing values in a single call. It is ideal for pre-reporting data quality workflows where source/target totals must be compared across groups and dates without nulls. Prefer it over generic pivot tools when you specifically need the combined pivot + imputation output as two structured reports at low cost ($0.01 USDC for both). Not suitable for live data lookups, predictions, or datasets exceeding 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:57.429Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-date-category-pivot-missing-value-fill-7b8879bf"}