{"uid":"cap_RjdPV2zqPDriJvq3niDBK","slug":"join-coverage-analytics-numeric-row-ordering-two-measure-correlation-496a48b5","name":"Join Coverage Analytics: Numeric Row Ordering + Two-Measure Correlation","description":"Join coverage — Numeric row ordering + Two-measure correlation: Numeric row ordering + Two-measure correlation 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-09-120?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_j1xee5C15A_V_qUhdRoFc","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":"Analyzes join coverage records by computing numeric row ordering and Pearson/rank correlation between matched_rows and source_rows for up to 200 supplied data rows.","exampleAgentPrompt":"Can you analyze my join coverage data and give me both a numeric row ordering and a two-measure correlation between matched_rows and source_rows? Here are my records: row-1 on 2026-10-01 in group-a had 10 matched and 1 source, row-2 on 2026-10-02 in group-b had 20 matched and 2 source, row-3 on 2026-10-03 in group-a had 15 matched and 3 source — focus the analysis on matched_rows.","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I have 50 rows of join coverage data from our nightly ETL run across two dataset groups — can you rank them by numeric row order and tell me how correlated the matched_rows are with source_rows? I'll give you the row IDs, dates, and counts."},{"title":"Data team join coverage correlation check","prompt":"We're debugging a data pipeline and want to know if matched_rows and source_rows move together across our dataset groups. Can you run a two-measure correlation and numeric ordering analysis on these 30 join coverage records?"},{"title":"Monthly join metric trend analysis","prompt":"Can you take my join coverage records for October — about 80 rows split across group-a and group-b — and produce a numeric ordering plus a correlation report between source_rows and matched_rows so I can see if the join rate is consistent?"}],"resultDescription":"Returns two independent analytical reports for the supplied join coverage rows: (1) a numeric row ordering of the records, and (2) a two-measure correlation analysis between matched_rows and source_rows. Reports are computed locally on the supplied data with no external lookup.","failureModes":["Fewer than 1 row supplied — validation error","More than 200 rows supplied — request rejected","Invalid date format (not YYYY-MM-DD) — schema validation failure","Null values in both matched_rows and source_rows — correlation computation may be undefined","Missing required fields (row_id, dataset_group, date) — schema rejection","Non-numeric values in matched_rows or source_rows — type error"],"whenToPreferThis":"Choose this endpoint when you have pre-collected join coverage data (matched_rows, source_rows) and need both a numeric ordering of records and a statistical correlation between the two measures in a single paid call. It is best suited for data engineers and analysts validating ETL pipeline join quality across dataset groups and dates, where no external data lookup or live prediction is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:32.481Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-row-ordering-two-measure-correlation-496a48b5"}