{"uid":"cap_U5zcuIsOTFBjOHbvGadPX","slug":"join-coverage-analytics-numeric-distribution-trailing-mean-series-34fbd66f","name":"Join Coverage Analytics: Numeric Distribution + Trailing Mean Series","description":"Join coverage — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series 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-09-076?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_2qcF3TEu2scJvEJ_KAbVv","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 report and a trailing mean time series for join coverage metrics (matched_rows, source_rows) across up to 200 supplied rows.","exampleAgentPrompt":"Can you run a numeric distribution and trailing mean analysis on my join coverage data? I have 50 records with matched_rows and source_rows by date and dataset group — analyze the matched_rows field with a window of 7.","exampleUseCases":[{"title":"Monitoring join match rate trends","prompt":"I want to see how our join coverage has been trending — here are 120 daily records with matched_rows and source_rows across two dataset groups. Give me the numeric distribution and a 14-day trailing mean for matched_rows."},{"title":"Profiling source row volume distribution","prompt":"Can you profile the distribution of source_rows across my 80 join coverage records and also show me a trailing mean with a window of 5, so I can spot any anomalies in volume?"},{"title":"QA check on ETL join completeness","prompt":"We're doing a QA pass on our ETL pipeline joins — here are 200 records with matched_rows and source_rows by date and group. Run the numeric distribution and trailing mean (window 10) on matched_rows so we can review the stats before sign-off."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric distribution profile of the selected field (matched_rows or source_rows), covering statistical descriptors such as min, max, mean, percentiles, and histogram-style bucketing; and (2) a trailing mean time series computed over the specified window size, showing smoothed trends across the supplied date-ordered records. Both reports are derived purely from the submitted data with no external lookups.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — request rejected","Window size larger than number of rows — trailing mean may be undefined or partially computed","Missing required fields (row_id, date, matched_rows, source_rows, dataset_group) — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Field value outside allowed numeric range — validation error","Payment not received or insufficient USDC — 402 payment required error"],"whenToPreferThis":"Choose this endpoint when you have preloaded join coverage records (matched_rows and source_rows) and need both a distributional statistical profile AND a rolling mean trend in a single low-cost call. It is ideal for data engineers or analysts doing offline QA, trend monitoring, or ETL validation on batch data snapshots without needing live database access or external enrichment. Prefer it over single-report endpoints when you want both distribution and time-series smoothing in one $0.01 payment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:27.421Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-distribution-trailing-mean-series-34fbd66f"}