{"uid":"cap_j5rRw4r8pjbQvSkE4b1bO","slug":"pipeline-durations-analytics-two-measure-correlation-secondary-6e1aa472","name":"Pipeline Durations Analytics: Two-Measure Correlation + Secondary-Measure Weighted Mean","description":"Pipeline durations — Two-measure correlation + Secondary-measure weighted mean: Two-measure correlation + 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-05-181?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_IxCcDQqHg5Z7dwM-tj9Qu","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 Pearson correlation between run_seconds and processed_rows, plus a weighted mean for a chosen secondary measure, across up to 200 pipeline duration records.","exampleAgentPrompt":"I have pipeline run data with run_seconds and processed_rows for about 50 jobs — can you calculate the correlation between run time and rows processed, plus the weighted mean of processed_rows across all runs?","exampleUseCases":[{"title":"ETL pipeline efficiency correlation check","prompt":"I've got 120 rows of ETL job records with run_seconds and processed_rows fields — can you run a correlation analysis to see how strongly run time relates to row count, and also give me a weighted mean for processed_rows?"},{"title":"Data ingestion pipeline performance review","prompt":"Here are our nightly ingestion pipeline records for the past quarter, each with run_seconds and processed_rows. Can you compute the two-measure correlation between those fields and a weighted mean for run_seconds so I can spot inefficiencies?"},{"title":"Multi-group pipeline comparison","prompt":"I have pipeline runs from two dataset groups — group-a and group-b — with up to 80 records each, all tagged with dates, run_seconds, and processed_rows. Can you correlate run time against rows processed and give me the weighted mean for processed_rows across all of them?"}],"resultDescription":"Returns two analytical reports sharing local computation: (1) a Pearson or similar correlation coefficient between run_seconds and processed_rows across the supplied rows, and (2) a weighted mean for the chosen secondary measure field (run_seconds or processed_rows). No external lookups or predictions are made; results are derived purely from the submitted data.","failureModes":["Fewer than 1 row supplied — minimum items validation error","More than 200 rows submitted — maxItems exceeded error","Missing required fields (row_id, date, run_seconds, processed_rows, dataset_group) cause schema validation failure","Invalid date format (not YYYY-MM-DD) triggers pattern validation error","Null values in both numeric fields may cause degenerate correlation results","Payment of 0.01 USDC not provided or x402 protocol not followed — payment required error"],"whenToPreferThis":"Choose this endpoint when you have tabular pipeline duration data (run_seconds + processed_rows) and need both a correlation analysis and a weighted mean in a single low-cost call. It is ideal for data engineers wanting quick offline statistical summaries without setting up local tooling or making external predictions. Prefer it over general-purpose statistics APIs when your data fits the pipeline duration schema and you want two reports for a flat $0.01 USDC fee.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:06.118Z","isFirstParty":false,"canonicalSlug":"pipeline-durations-analytics-two-measure-correlation-secondary-6e1aa472"}