{"uid":"cap_lyYTNqbs0jW17RhvtZ53x","slug":"transformation-throughput-numeric-row-ordering-iqr-outlier-flags-5d1c3ddc","name":"Transformation Throughput — Numeric Row Ordering + IQR Outlier Flags","description":"Transformation throughput — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-119?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_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_3owQqv-eNdNrIL2KsDFm4","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":"Ranks transformation throughput records by processed_rows or duration_seconds and flags statistical outliers using the interquartile range (IQR) method, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Analyze my transformation throughput records — I have up to 50 rows each with a row_id, dataset_group, date, processed_rows, and duration_seconds — rank them by processed_rows and flag any IQR outliers across both metrics.","exampleUseCases":[{"title":"ETL pipeline anomaly detection","prompt":"I have logs from my nightly ETL runs with row_id, date, dataset_group, processed_rows, and duration_seconds — can you rank them by processed_rows and flag any statistically unusual jobs using IQR outlier detection?"},{"title":"Pipeline duration outlier audit","prompt":"Here are 120 transformation job records from last quarter. Sort them by duration_seconds and highlight which runs were outliers based on IQR so I can investigate what caused the slow ones."},{"title":"Dataset group throughput ranking","prompt":"I want to compare throughput across my dataset groups — I'll send you records with processed_rows and duration_seconds per run, ranked by processed_rows, and I need IQR-based outlier flags so I can spot which groups are performing abnormally."}],"resultDescription":"Returns two analytical reports: (1) rows ordered numerically by the selected field (processed_rows or duration_seconds), and (2) IQR-based outlier flags identifying records that fall below Q1−1.5×IQR or above Q3+1.5×IQR. No external lookups or predictions are made; analysis is entirely local to the supplied data.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — request rejected","Missing required fields (row_id, date, processed_rows, duration_seconds) — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Non-numeric values in processed_rows or duration_seconds — type error","Invalid field enum value (not 'processed_rows' or 'duration_seconds') — enum validation error","All values identical — IQR is zero, no outliers flagged (degenerate case)"],"whenToPreferThis":"Choose this endpoint when you have tabular transformation throughput records (ETL job logs, pipeline run metrics) and need both a sorted ranking and IQR-based outlier detection in a single call, without requiring any external data, live predictions, or professional assessment. It is best suited for offline batch analysis of up to 200 rows where two simultaneous statistical reports on processed_rows and duration_seconds are needed cost-effectively.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:56.404Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-numeric-row-ordering-iqr-outlier-flags-5d1c3ddc"}