{"uid":"cap_IfOOahHqnJserLebu68pl","slug":"data-reconciliation-daily-sum-series-date-by-category-pivot-196ae9b8","name":"Data Reconciliation — Daily Sum Series + Date by Category Pivot","description":"Data reconciliation — Daily sum series + Date by category pivot: Daily sum series + Date by category pivot 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-11-143?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"}}},"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_1xLtdrsWKxyELvVQktzOK","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":"Generates two analytical reports from supplied reconciliation data: a daily sum time series and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"I have reconciliation records with source and target totals across multiple dataset groups — can you run the daily sum series and date-by-category pivot reports on this data so I can see where the numbers diverge? Here are the rows: [{\"row_id\":\"r1\",\"date\":\"2025-01-01\",\"dataset_group\":\"sales\",\"source_total\":500,\"target_total\":480},{\"row_id\":\"r2\",\"date\":\"2025-01-02\",\"dataset_group\":\"sales\",\"source_total\":620,\"target_total\":610}], and use source_total as the primary field.","exampleUseCases":[{"title":"Daily ETL pipeline discrepancy review","prompt":"I've got ETL reconciliation records across two groups — 'warehouse' and 'crm' — for the past month. Can you run both the daily sum series and the date-by-category pivot on my source_total values so I can spot where the pipeline is dropping numbers?"},{"title":"Finance team source vs target audit","prompt":"We need to audit our source_total vs target_total reconciliation data for Q1 across three dataset groups. Can you produce the daily sums time series and a pivot by date and category from these records so the finance team can review the gaps?"},{"title":"Data migration validation report","prompt":"We just completed a data migration and I need to validate the results. Here are our reconciliation rows with source and target totals by date and group — please generate the daily aggregated sums and a date-by-category pivot for target_total so we can confirm the migration landed correctly."}],"resultDescription":"Returns two independent analytical reports computed locally from the supplied rows: (1) a daily sum series showing aggregated values of the selected field (source_total or target_total) per date, and (2) a date-by-category pivot table breaking down values by date and dataset_group. Supports up to 200 input rows per call.","failureModes":["Input array exceeds 200 rows — request will be rejected","Missing required fields (row_id, dataset_group, date, source_total, target_total) on any row causes validation failure","Invalid date format (must be YYYY-MM-DD) causes schema rejection","Null values in source_total or target_total may affect aggregation results","Invalid field enum value (must be 'source_total' or 'target_total') causes rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 pre-collected reconciliation records with source and target totals and need both a daily time series aggregation and a date-by-category pivot in a single low-cost call ($0.01 USDC). Ideal for ETL validation, finance audits, and data migration checks where you already have the data locally and need fast offline analytics without any external lookup or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:53.036Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-daily-sum-series-date-by-category-pivot-196ae9b8"}