{"uid":"cap_fyq4QCkDxXSeytqY-TKZ6","slug":"data-reconciliation-grouped-numeric-summary-iqr-outlier-flags-d08ae3f4","name":"Data Reconciliation — Grouped Numeric Summary + IQR Outlier Flags","description":"Data reconciliation — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags 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-11-094?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_SGZsILoENu35EM7rP0Gi1","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":"Computes grouped descriptive statistics and flags IQR-based outliers for up to 200 data reconciliation rows comparing source_total vs target_total values, producing two independent analytical reports.","exampleAgentPrompt":"Can you analyze these reconciliation records and give me a grouped numeric summary plus IQR outlier flags for the source_total field? I have up to 50 rows with columns row_id, dataset_group, date, source_total, and target_total.","exampleUseCases":[{"title":"Finance team ETL reconciliation audit","prompt":"I have 120 daily reconciliation rows from our ETL pipeline with source_total and target_total values across three dataset groups — can you compute a grouped numeric summary and flag any IQR outliers in source_total so I can spot which groups have problematic discrepancies?"},{"title":"Data quality check before month-end close","prompt":"Before we close the books, run a grouped statistical summary and IQR outlier detection on our 80 reconciliation records — grouped by dataset_group — and flag any rows where the target_total looks anomalous."},{"title":"Cross-system data validation for two data sources","prompt":"We're validating two data sources and I have 45 reconciliation rows with source_total and target_total — can you produce a grouped numeric summary and flag IQR outliers in the target_total column so we can see which groups have the biggest mismatches?"}],"resultDescription":"Returns two independent analytical reports: (1) a grouped numeric summary (e.g. count, mean, median, std, min, max) segmented by dataset_group for the chosen field, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range, all computed locally with no external data access.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, dataset_group, date, source_total, target_total) causes validation error","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Numeric values outside ±1,000,000,000,000 range rejected by schema","Empty rows array returns error","All-null values in the selected field may produce degenerate statistics"],"whenToPreferThis":"Choose this endpoint when you need both grouped descriptive statistics AND IQR-based outlier detection on reconciliation data (source vs target totals) in a single call for up to 200 rows, at very low cost ($0.01 USDC for 2 reports). Prefer it over general-purpose analytics when you specifically have reconciliation-style records with source/target numeric pairs grouped by a categorical dimension and want flagging without external API dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:47:07.534Z","isFirstParty":false,"canonicalSlug":"data-reconciliation-grouped-numeric-summary-iqr-outlier-flags-d08ae3f4"}