{"uid":"cap_HY4oY1Q4mUzNBqnIyoX5L","slug":"join-coverage-analytics-numeric-distribution-weighted-mean-84e36274","name":"Join Coverage Analytics — Numeric Distribution & Weighted Mean","description":"Join coverage — Numeric distribution + Secondary-measure weighted mean: Numeric distribution + Secondary-measure weighted mean for supplied join coverage records (matched_rows, source_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-09-082?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_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_yWdyTgPvvPtIiJcrKDRRD","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 a numeric distribution and secondary-measure weighted mean for join coverage records (matched_rows, source_rows) across up to 200 supplied rows.","exampleAgentPrompt":"Can you run a join coverage analysis on these 4 rows — group-a had 10 matched vs 1 source on 2026-10-01 and 15 matched vs 3 source on 2026-10-03, group-b had 20 matched vs 2 source on 2026-10-02 and 30 matched vs 4 source on 2026-10-04 — and give me the numeric distribution plus weighted mean for the matched_rows field?","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I have daily join coverage records for two dataset groups over last week — each row has a date, group name, matched_rows, and source_rows. Can you compute the numeric distribution and weighted mean for matched_rows across all those rows so I can see where join quality is high or low?"},{"title":"Dataset coverage discrepancy investigation","prompt":"I'm seeing inconsistencies in how many source rows vs matched rows we get for group-a and group-b. Can you analyze these 12 records and give me the distribution and secondary-measure weighted mean for source_rows so I can pinpoint which dates have coverage gaps?"},{"title":"Multi-group join ratio summary report","prompt":"We have join coverage data from four dataset groups across Q4 — about 150 rows total with matched_rows and source_rows per date. Please give me the numeric distribution and weighted mean for matched_rows so I can build a coverage summary report for the engineering review."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric distribution of the selected field (matched_rows or source_rows) across all supplied rows, and (2) a secondary-measure weighted mean — both computed locally on the up-to-200 supplied join coverage records with no external lookups.","failureModes":["Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors","Supplying more than 200 rows exceeds the maxItems limit and will be rejected","Invalid date format (not YYYY-MM-DD) fails pattern validation","Null values in both matched_rows and source_rows may degrade weighted mean calculation","field enum value other than 'matched_rows' or 'source_rows' causes a validation error"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical analysis of join coverage data — specifically numeric distributions and weighted means for matched_rows or source_rows — without any external data lookup or prediction. Ideal for data engineers auditing ETL join quality, data quality analysts investigating coverage gaps, or pipeline monitoring workflows that already have join coverage records in hand and need a cheap ($0.01 USDC), reproducible analytical summary across up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:38.689Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-distribution-weighted-mean-84e36274"}