{"uid":"cap_S7iG4kuEG1WICNQaBQvr1","slug":"data-ingestion-batches-grouped-numeric-summary-iqr-outlier-flags-fd175c95","name":"Data Ingestion Batches — Grouped Numeric Summary + IQR Outlier Flags","description":"Data ingestion batches — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied data ingestion batches records (received_rows, accepted_rows). 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-01-094?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","received_rows","accepted_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"accepted_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"received_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","accepted_rows":1,"dataset_group":"group-a","received_rows":10},{"date":"2026-10-02","row_id":"row-2","accepted_rows":2,"dataset_group":"group-b","received_rows":20},{"date":"2026-10-03","row_id":"row-3","accepted_rows":3,"dataset_group":"group-a","received_rows":15},{"date":"2026-10-04","row_id":"row-4","accepted_rows":4,"dataset_group":"group-b","received_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["received_rows","accepted_rows"],"type":"string","default":"received_rows"}}},"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_PPMBEM4AJExpuIiuvImZV","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 IQR-based outlier flags for up to 200 data ingestion batch records across received_rows and accepted_rows fields.","exampleAgentPrompt":"Can you analyze my data ingestion batch records — I have about 50 rows with dataset_group, date, received_rows, and accepted_rows — and give me a grouped numeric summary plus IQR outlier flags for the received_rows field?","exampleUseCases":[{"title":"Pipeline quality monitoring by group","prompt":"I have 120 ingestion batch records from last month, each tagged with a dataset_group and daily date, and I want a grouped summary of accepted_rows — mean, median, quartiles — plus IQR outlier flags so I can see which groups had abnormal acceptance rates."},{"title":"Detecting anomalous data loads","prompt":"Can you flag which of my ingestion batches have received_rows that look like statistical outliers using the IQR method? I'll send you the rows with row_id, dataset_group, date, and received_rows values."},{"title":"Comparing ingestion throughput across datasets","prompt":"I want to compare received_rows and accepted_rows across my three dataset groups — group-a, group-b, and group-c — using about 80 daily batch records. Give me a grouped numeric summary and highlight any IQR-based outliers in the accepted_rows field."}],"resultDescription":"Returns two analytical reports (one per numeric field or configured field selection): grouped descriptive statistics (mean, median, quartiles, etc.) broken down by dataset_group, plus IQR-based outlier flags identifying which individual rows fall outside expected ranges. Covers up to 200 input rows with no external lookups or live data.","failureModes":["Input exceeds 200 rows — request will be rejected","Missing required fields (row_id, dataset_group, date, received_rows, accepted_rows) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Numeric values outside allowed range (-1T to +1T) are rejected","Empty rows array returns an error","Null numeric values may affect statistical computation accuracy"],"whenToPreferThis":"Choose this endpoint when you need fast, offline grouped statistical summaries and IQR outlier detection specifically for data ingestion pipeline records (received_rows, accepted_rows) without requiring external data sources, ML models, or real-time lookups. Ideal for batch QA checks on ingestion logs up to 200 records at $0.01 per call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:25.904Z","isFirstParty":false,"canonicalSlug":"data-ingestion-batches-grouped-numeric-summary-iqr-outlier-flags-fd175c95"}