{"uid":"cap_3pTYs6vsrCFd5yT0CHSZI","slug":"transformation-throughput-trailing-mean-series-iqr-outlier-flags-6318719e","name":"Transformation Throughput — Trailing Mean Series + IQR Outlier Flags","description":"Transformation throughput — Trailing mean series + IQR outlier flags: Trailing mean series + 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-13-149?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_03H43JmpBfP5pSQ_yeVUA","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 trailing mean time series and IQR-based outlier flags for transformation throughput records (processed_rows or duration_seconds) over up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"Analyze my transformation throughput records for processed_rows with a trailing window of 5 — here are my rows: [{\"row_id\":\"r1\",\"dataset_group\":\"etl-prod\",\"date\":\"2024-01-01\",\"processed_rows\":1000,\"duration_seconds\":30}, ...] — flag any IQR outliers and give me the trailing mean series.","exampleUseCases":[{"title":"ETL pipeline anomaly detection","prompt":"I have 120 daily ETL run records with processed_rows and duration_seconds. Can you run the trailing mean series with a window of 7 and flag any IQR outliers in the processed_rows field so I can spot which runs behaved abnormally?"},{"title":"Batch job duration trend analysis","prompt":"Here are 90 transformation job records — please compute the trailing mean series for duration_seconds using a window of 10 and tell me which runs are flagged as outliers by the IQR method."},{"title":"Data quality check on throughput variance","prompt":"My team wants to review throughput consistency across two dataset groups over the last 60 runs. Can you analyze processed_rows with a trailing window of 5 and highlight any IQR-flagged outliers in the results?"}],"resultDescription":"Two analytical reports: (1) a trailing mean time series for the selected field (processed_rows or duration_seconds) computed over the specified window size, and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range — both derived entirely from the supplied input rows with no external lookups.","failureModes":["Fewer than 1 row supplied — minimum 1 row required","More than 200 rows supplied — maxItems limit exceeded","Invalid date format (must be YYYY-MM-DD)","Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds)","Window size less than 2 or greater than 200","Payment failure via x402 protocol — endpoint returns 402 if USDC payment not confirmed","Null numeric values may affect trailing mean computation"],"whenToPreferThis":"Choose this endpoint when you need both a rolling/trailing mean time series AND IQR outlier detection on ETL or data transformation throughput metrics (processed_rows or duration_seconds) in a single call. It is purpose-built for pipeline performance analytics on supplied historical records — not for live monitoring, predictions, or non-throughput datasets. Prefer it over general statistics APIs when you specifically need the IQR+trailing-mean combination on transformation job data with up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:50.207Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-trailing-mean-series-iqr-outlier-flags-6318719e"}