{"uid":"cap_w_xuVKvAEL7cyU2sHLsHY","slug":"join-coverage-analytics-trailing-mean-series-missing-value-fill-c85aeb9e","name":"Join Coverage Analytics: Trailing Mean Series + Missing-Value Fill","description":"Join coverage — Trailing mean series + Explicit missing-value fill: Trailing mean series + 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-09-154?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"},"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_zRONorsTcOY5cgU6CKpuD","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 trailing mean time series and fills missing values for join coverage records (matched_rows, source_rows) across up to 200 rows in two bundled reports.","exampleAgentPrompt":"I have daily join coverage records for two dataset groups over the past week with matched_rows and source_rows counts — can you run a trailing mean series with a window of 7 and fill any missing matched_rows values using the mean method on up to 50 rows?","exampleUseCases":[{"title":"Smoothing noisy pipeline join metrics","prompt":"My ETL pipeline produces daily matched_rows and source_rows counts per dataset group and there are big day-to-day swings — can you compute a trailing mean over a window of 5 days for the matched_rows field and fill any nulls with the mean so I can see the smoothed trend?"},{"title":"Auditing data completeness for join coverage","prompt":"I've got 120 rows of join coverage data across several dataset groups with some missing source_rows values — run a trailing mean series with window 3 and fill the missing source_rows using median so I can audit where coverage drops."},{"title":"Preparing join metrics for dashboard reporting","prompt":"Before I push our weekly join coverage numbers to the dashboard, I need a trailing mean with window 10 on matched_rows plus explicit zero-fill for any missing values — can you process these 80 rows grouped by dataset_group?"}],"resultDescription":"Returns two analytical reports per call: (1) a trailing mean time series for the selected field (matched_rows or source_rows) computed over the specified window size across the supplied rows, and (2) the same dataset with explicit missing-value fills applied using the chosen method (zero, mean, or median). Both reports are computed locally with no external data lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Invalid date format (non-YYYY-MM-DD) causes row validation failure","Window size larger than the number of rows produces incomplete or empty trailing series","All values null for a field with mean/median fill yields no imputed values","Missing required fields (row_id, date, dataset_group) cause row-level errors"],"whenToPreferThis":"Choose this endpoint when you need both trailing mean smoothing and explicit missing-value imputation for join coverage metrics (matched_rows/source_rows) in a single call at low cost. Ideal for small-to-medium datasets (up to 200 rows) where you need local, deterministic statistical processing without external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:19.108Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-trailing-mean-series-missing-value-fill-c85aeb9e"}