{"uid":"cap_g522n9baEHPZXA86Ig2n5","slug":"join-coverage-analytics-numeric-row-ordering-trailing-mean-series-8c7b7c56","name":"Join Coverage Analytics — Numeric Row Ordering + Trailing Mean Series","description":"Join coverage — Numeric row ordering + Trailing mean series: Numeric row ordering + 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-09-115?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_0azmMinGxtTpDoD-OCcDN","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 numeric row ordering and trailing mean series for join coverage records (matched_rows, source_rows) across up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Analyze my join coverage data for group-a and group-b across these 4 dates in October 2026 — rank the rows numerically by matched_rows and compute a trailing mean with a window of 2. Here are the records: row-1 (2026-10-01, source=1, matched=10), row-2 (2026-10-02, source=2, matched=20), row-3 (2026-10-03, source=3, matched=15), row-4 (2026-10-04, source=4, matched=30).","exampleUseCases":[{"title":"ETL pipeline coverage trending","prompt":"I have join coverage records from my ETL pipeline for the past week across two dataset groups — can you rank the rows by matched_rows and compute a trailing mean with a window of 3 so I can see which days had the best coverage?"},{"title":"Data quality audit for source rows","prompt":"Run a numeric row ordering and trailing mean analysis on my source_rows join coverage data — I have 8 records across dataset groups 'inventory' and 'orders' from 2026-09-01 to 2026-09-08, window size 2. I want to spot anomalies in how source row counts changed over time."},{"title":"Comparing matched vs source row trends","prompt":"I want to understand the trend in my matched_rows for join coverage across 'region-east' and 'region-west' groups over 10 daily records in October 2026 — give me both the numeric ranking and the rolling mean with window 4."}],"resultDescription":"Returns two independent analytical reports: (1) a numeric row ordering of the supplied join coverage records ranked by the selected field (matched_rows or source_rows), and (2) a trailing mean series computed over the specified window size for the same field — both derived from the user-supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds max item limit","Window size exceeds number of rows — trailing mean may be undefined for early rows","Invalid date format (not YYYY-MM-DD) — schema validation failure","Missing required fields (row_id, dataset_group, date) — validation error","Null values in matched_rows or source_rows — may produce null entries in output series"],"whenToPreferThis":"Choose this endpoint when you need both numeric row ranking and a rolling/trailing mean analysis on join coverage metrics (matched_rows or source_rows) in a single low-cost call. Ideal for data engineers auditing ETL pipeline join quality over time, especially when you have up to 200 timestamped records grouped by dataset and want two complementary views — ordering and trend smoothing — without any external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:35.535Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-row-ordering-trailing-mean-series-8c7b7c56"}