{"uid":"cap_GUEvLtlai-rWklJOlrBex","slug":"time-series-completeness-exact-row-deduplication-trailing-mean-series-c178bfd4","name":"Time Series Completeness — Exact Row Deduplication + Trailing Mean Series","description":"Time series completeness — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series for supplied time series completeness records (observed_points, expected_points). 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-16-045?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","observed_points","expected_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_points":1,"observed_points":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_points":2,"observed_points":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_points","expected_points"],"type":"string","default":"observed_points"},"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_AyKrGH3iH88uc0Zd5_U0l","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 time series completeness records by performing exact row deduplication and computing a trailing mean series for observed vs. expected data points, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you deduplicate these time series completeness records and run a trailing mean series with a window of 3 on the observed_points field? I have up to 50 rows across two dataset groups, each with a date, observed_points, and expected_points.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I have 80 rows of daily completeness records for two dataset groups — each row has a date, observed_points, and expected_points. Can you deduplicate them and compute a trailing mean with a window of 7 on observed_points so I can spot where data delivery was consistently below expectations?"},{"title":"Trailing mean smoothing for monitoring dashboard","prompt":"Take these 120 time series rows with observed and expected data points across several dataset groups, deduplicate any exact duplicate rows, then compute a trailing mean series over expected_points with a window size of 5 — I want to use this to smooth out my completeness monitoring charts."},{"title":"QA check on ingestion completeness logs","prompt":"I've got 30 daily completeness log entries per dataset group and I want to find and remove any exact duplicate rows, then calculate a rolling mean with window 2 on observed_points to help QA our ingestion pipeline — can you run both reports?"}],"resultDescription":"Returns two reports: (1) a deduplicated version of the input rows with exact duplicates removed, and (2) a trailing mean series computed over the specified field (observed_points or expected_points) using the given window size — all derived locally without external lookups or predictions.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, date, observed_points, expected_points) in one or more rows — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Window size outside allowed range (2–200) — parameter error","All rows are duplicates — deduplication report returns empty or minimal dataset","Payment not completed via x402 — endpoint returns 402 response"],"whenToPreferThis":"Use this endpoint when you need both exact row deduplication and a trailing mean series computed together on time series completeness data (observed vs. expected points) in a single low-cost call. It is ideal for data quality workflows, pipeline monitoring, and completeness audits where local computation — without external lookups, predictions, or live data — is sufficient. Best when your dataset fits within 200 rows and you want two complementary analytical views returned at once for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:06.758Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-exact-row-deduplication-trailing-mean-series-c178bfd4"}