{"uid":"cap_yOSTQhpm_odspzN4WTSDA","slug":"pipeline-durations-analytics-numeric-row-ordering-weighted-mean-2006d8a8","name":"Pipeline Durations Analytics — Numeric Row Ordering & Weighted Mean","description":"Pipeline durations — Numeric row ordering + Secondary-measure weighted mean: Numeric row ordering + Secondary-measure weighted mean for supplied pipeline durations records (run_seconds, processed_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-05-121?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","run_seconds","processed_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"run_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","run_seconds":10,"dataset_group":"group-a","processed_rows":1},{"date":"2026-10-02","row_id":"row-2","run_seconds":20,"dataset_group":"group-b","processed_rows":2},{"date":"2026-10-03","row_id":"row-3","run_seconds":15,"dataset_group":"group-a","processed_rows":3},{"date":"2026-10-04","row_id":"row-4","run_seconds":30,"dataset_group":"group-b","processed_rows":4}],"maxItems":200,"minItems":1},"field":{"enum":["run_seconds","processed_rows"],"type":"string","default":"run_seconds"}}},"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_B2hPo_ai5mObeURureyLM","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 numeric row ordering and secondary-measure weighted mean for pipeline duration records (run_seconds, processed_rows) on up to 200 supplied rows.","exampleAgentPrompt":"Can you rank these pipeline runs by their run_seconds and also compute the weighted mean of run_seconds using processed_rows as the weight? Here are my records: row-1 on 2024-01-01, group-a, 120 seconds, 500 rows; row-2 on 2024-01-02, group-b, 200 seconds, 1000 rows; row-3 on 2024-01-03, group-a, 90 seconds, 300 rows.","exampleUseCases":[{"title":"ETL job duration ranking","prompt":"I have a list of ETL pipeline runs with their durations and rows processed — can you give me a numeric ordering of the runs by run_seconds and also compute the weighted mean of run_seconds using processed_rows as the weight? Runs: job-A on 2024-03-01, team-alpha, 450 seconds, 2000 rows; job-B on 2024-03-02, team-beta, 300 seconds, 1500 rows; job-C on 2024-03-03, team-alpha, 600 seconds, 5000 rows."},{"title":"Data pipeline performance summary","prompt":"Here are 5 pipeline execution records from last week — please rank them numerically by processed_rows and calculate the weighted mean of processed_rows weighted by run_seconds: pipe-1, 2024-06-10, group-x, 80s, 400 rows; pipe-2, 2024-06-11, group-y, 150s, 900 rows; pipe-3, 2024-06-12, group-x, 60s, 200 rows; pipe-4, 2024-06-13, group-z, 200s, 1200 rows; pipe-5, 2024-06-14, group-y, 120s, 700 rows."},{"title":"Cross-group pipeline comparison","prompt":"Can you order these pipeline runs across two dataset groups by run_seconds and compute a weighted mean of run_seconds using processed_rows? batch-1, 2024-09-01, finance, 500s, 10000 rows; batch-2, 2024-09-02, marketing, 350s, 7000 rows; batch-3, 2024-09-03, finance, 420s, 8500 rows; batch-4, 2024-09-04, marketing, 280s, 5000 rows."}],"resultDescription":"Returns two analytical reports: (1) numeric row ordering of the supplied pipeline records ranked by the selected field (run_seconds or processed_rows), and (2) a secondary-measure weighted mean where the chosen field is averaged using the other measure as weights. Both reports are computed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows supplied — request rejected due to maxItems constraint","Missing required fields (row_id, dataset_group, date, run_seconds, processed_rows) cause validation errors","Null values in run_seconds or processed_rows may affect weighted mean computation","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Invalid field enum value (not run_seconds or processed_rows) causes rejection"],"whenToPreferThis":"Choose this endpoint when you have pipeline execution records with duration and row-count fields and need both a numeric ranking of runs and a rows-weighted mean computed locally without any external data calls. Ideal for data engineers analyzing ETL performance across groups where you want two complementary statistical views (ordering + weighted average) in a single cheap call ($0.01 USDC for up to 200 rows).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:41:07.978Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-analytics-numeric-row-ordering-weighted-mean-2006d8a8"}