{"uid":"cap_9tAd_eH3SRCzUmDrdfX6q","slug":"join-coverage-two-measure-correlation-and-missing-value-fill-2c39e7b3","name":"Join Coverage Two-Measure Correlation and Missing-Value Fill","description":"Join coverage — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill 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-09-184?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_sb_O0U5nM44U5iryDd6VM","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 matched_rows and source_rows join coverage metrics, and fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 supplied rows.","exampleAgentPrompt":"I have up to 200 rows of join coverage data with matched_rows and source_rows per dataset group and date — can you run a two-measure correlation on them and fill any missing matched_rows values using median imputation?","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"Here are 150 rows of my ETL join coverage data with matched_rows and source_rows across two dataset groups from last quarter — run the correlation analysis and fill any null matched_rows with the median so I can see if my joins are consistent."},{"title":"Data completeness check before reporting","prompt":"I have a CSV of daily join coverage records with some missing source_rows values — can you fill those nulls using zero substitution and also tell me how correlated matched_rows and source_rows are across my groups?"},{"title":"Multi-group join coverage investigation","prompt":"We're seeing inconsistent join rates across group-a and group-b in our data warehouse — send these 80 rows through the two-measure correlation and use mean fill for any missing matched_rows to help us diagnose the issue."}],"resultDescription":"Two structured analytical reports: (1) a Pearson correlation result between matched_rows and source_rows across the supplied dataset, and (2) a version of the chosen measure field with explicit missing-value fills applied using the specified method (zero, mean, or median). Results are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Unsupported imputation method value outside zero/mean/median enum — rejected","All values in both measures are null — correlation cannot be computed, partial or error response","Payment not included or insufficient (requires 0.01 USDC via x402) — 402 response"],"whenToPreferThis":"Choose this endpoint when you have tabular join coverage data with matched_rows and source_rows columns and need both a correlation analysis and missing-value imputation in a single call without external data lookups. It is purpose-built for data engineering and ETL quality workflows where you want local statistical computation on supplied data at low cost. Prefer alternatives if you need more than two measures analyzed simultaneously, more than 200 rows processed, or external data sources consulted.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:29.962Z","isFirstParty":false,"canonicalSlug":"join-coverage-two-measure-correlation-and-missing-value-fill-2c39e7b3"}