{"uid":"cap_96T4V12e8UzWfxitgrKFA","slug":"data-reconciliation-numeric-row-ordering-explicit-missing-value-fill-e8e3ac21","name":"Data Reconciliation — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Data reconciliation — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + 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-11-124?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_NwTKJ4shFQYTS_j4Z4ZRw","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":"Sorts reconciliation rows numerically and fills missing source_total or target_total values using zero, mean, or median imputation for up to 200 records, returning two independent analytical reports.","exampleAgentPrompt":"I have a reconciliation dataset with up to 50 rows — each row has a row_id, dataset_group, date, source_total, and target_total, but some source_total values are missing. Can you sort the rows numerically and fill those missing source_total values using median imputation?","exampleUseCases":[{"title":"Impute missing source totals for monthly close","prompt":"I'm doing a month-end reconciliation and several of my source_total fields are null. Can you fill in those missing source_total values using median imputation and return the rows in numeric order? I'll send you up to 80 rows with row_id, dataset_group, date, source_total, and target_total."},{"title":"Clean target totals before audit review","prompt":"Before our audit, I need to fill any missing target_total entries in my reconciliation file using zero fill, then sort all the rows numerically. I have around 120 rows across two dataset groups — can you run that for me?"},{"title":"Mean-fill reconciliation data for dashboard","prompt":"My dashboard pipeline has gaps in the target_total column across about 30 reconciliation records. Can you apply mean imputation to those missing target_total values and order the rows numerically so I can load them cleanly?"}],"resultDescription":"Returns two independent analytical reports covering up to 200 reconciliation rows: one with rows sorted in numeric order, and one with missing values in the specified field (source_total or target_total) filled using the chosen method (zero, mean, or median). No external lookups or predictions are made — all computation uses the supplied data only.","failureModes":["More than 200 rows submitted — exceeds maximum row limit","Invalid date format not matching YYYY-MM-DD pattern","source_total or target_total values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)","Missing required fields (row_id, dataset_group, date) on any row","Invalid enum value for field or method parameters","Empty rows array submitted"],"whenToPreferThis":"Choose this endpoint when you need both numeric ordering and missing-value imputation applied to reconciliation data in a single call, with results delivered as two independent local reports. It is well-suited for financial or accounting reconciliation workflows where source and target totals need cleaning before comparison or audit, and no external data sources or predictions are required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:45:25.201Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-numeric-row-ordering-explicit-missing-value-fill-e8e3ac21"}