{"uid":"cap_8x7JOXvvVoV7DfJQPi1ED","slug":"join-coverage-analytics-daily-sum-series-two-measure-correlation-cf772293","name":"Join Coverage Analytics — Daily Sum Series & Two-Measure Correlation","description":"Join coverage — Daily sum series + Two-measure correlation: Daily sum series + 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-09-141?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_K0uVv9fby59Z4B8bl7ppC","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 daily sum time series and two-measure correlation analysis for join coverage data (matched_rows vs source_rows) supplied by the caller, up to 200 rows.","exampleAgentPrompt":"Can you run a daily sum series and correlation analysis on my join coverage data? I have rows with dates from 2026-10-01 to 2026-10-04 across groups 'group-a' and 'group-b', with matched_rows values like 10, 20, 15, 30 — use matched_rows as the primary field.","exampleUseCases":[{"title":"Daily join hit rate trending","prompt":"I have a week of join pipeline records for two dataset groups — can you compute the daily sum of matched_rows over time and tell me how correlated matched_rows and source_rows are across those days?"},{"title":"Source vs matched row correlation audit","prompt":"I want to understand whether my source row counts drive my matched row counts — run me a two-measure correlation between source_rows and matched_rows using this dataset, and also give me the daily totals for source_rows."},{"title":"Multi-group join coverage summary","prompt":"I've got join coverage records from three dataset groups over the past month, up to 150 rows. Can you give me a daily sum series and a correlation report for matched_rows vs source_rows so I can spot any coverage gaps?"}],"resultDescription":"Returns two analytical reports derived from the supplied row data: (1) a daily sum time series aggregating the selected field (matched_rows or source_rows) by date, and (2) a two-measure correlation analysis between matched_rows and source_rows — all computed locally from provided data with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) causes rejection","Invalid date format (non-YYYY-MM-DD) fails schema validation","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array not accepted (minItems: 1)","Payment not included or incorrect amount results in 402 response"],"whenToPreferThis":"Choose this endpoint when you have already-collected join coverage data (matched_rows and source_rows per date and group) and need both a daily aggregated time series AND a correlation analysis in a single low-cost call. It is ideal for data engineers auditing join pipeline quality over time who want two complementary analytical views without building their own stat engine. Prefer it over single-report alternatives when both time series and correlation are needed together.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:34.036Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-daily-sum-series-two-measure-correlation-cf772293"}