{"uid":"cap_AlUMsgylUEmayTUdMO0kX","slug":"data-reconciliation-numeric-interval-filter-two-measure-correlation-45d42e87","name":"Data Reconciliation — Numeric Interval Filter + Two-Measure Correlation","description":"Data reconciliation — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation 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-11-131?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_fZDCDSfZMsLWEF8cq8dsJ","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":"Filters reconciliation rows by a numeric interval on a chosen field and computes correlation between source_total and target_total, delivering two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"Run an interval filter on source_total between 0 and 50000, then compute the two-measure correlation between source_total and target_total for these reconciliation rows: row-1 (2024-01-01, group-a, source 12000, target 11800), row-2 (2024-01-02, group-b, source 45000, target 44200), row-3 (2024-01-03, group-a, source 62000, target 60500).","exampleUseCases":[{"title":"Monthly close source-target drift check","prompt":"I have 150 rows of month-end reconciliation data with source_total and target_total values. Filter to rows where target_total is between 10000 and 500000, and then tell me how strongly source_total and target_total are correlated across that filtered set."},{"title":"Detect mismatched group totals by range","prompt":"Here are my reconciliation records for Q1 across two dataset groups. Filter on source_total between -5000 and 5000 to isolate near-zero entries, and compute the correlation between source_total and target_total so I can see if small source values consistently match target values."},{"title":"Audit supplier invoice vs system totals","prompt":"I need to reconcile 80 supplier invoice rows against our system totals. Apply an interval filter on source_total from 0 to 100000, then run the two-measure correlation report between source_total and target_total so I can quantify how well the invoiced amounts align with what our system recorded."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric interval filter report listing which of the supplied reconciliation rows fall within the specified minimum–maximum range for the chosen field, and (2) a two-measure correlation report quantifying the statistical relationship between source_total and target_total across the submitted rows. Both reports are computed locally from the supplied data only — no external lookups or predictions.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — request rejected","source_total or target_total values outside ±1,000,000,000,000 — schema validation error","date field does not match YYYY-MM-DD pattern — validation error","field enum value not 'source_total' or 'target_total' — validation error","All values null for one measure — correlation computation may be undefined or return NaN","minimum greater than maximum — may yield empty filtered set with no error"],"whenToPreferThis":"Choose this endpoint when you have pre-assembled reconciliation row data (source_total vs target_total) and need both a range-based filter and a paired correlation analysis in a single $0.01 call. It is ideal for offline or batch reconciliation workflows where you already hold the data and want fast, local statistical insight without hitting a live database or prediction service. If you only need one type of analysis (e.g., just deduplication or just missing-value fill), a sibling endpoint with that single operation may be more cost-appropriate.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:47:03.320Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-numeric-interval-filter-two-measure-correlation-45d42e87"}