{"uid":"cap_Xq6kfGU8W3Evti-wf4c_m","slug":"time-series-completeness-numeric-distribution-secondary-measure-d9a69a16","name":"Time Series Completeness — Numeric Distribution + Secondary-Measure Weighted Mean","description":"Time series completeness — Numeric distribution + Secondary-measure weighted mean: Numeric distribution + Secondary-measure weighted mean 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-16-082?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"}}},"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_XENjfgqbCsqPoEdnYbXqd","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 distribution statistics and a secondary-measure weighted mean for time series completeness records (observed_points vs expected_points), producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you analyze the numeric distribution and compute a weighted mean for my time series completeness records? I have rows with observed_points and expected_points by date and dataset group — here's my data for up to 200 rows, and I want to focus on the observed_points field.","exampleUseCases":[{"title":"Daily pipeline completeness audit","prompt":"I have daily completeness records for my data pipelines — each row has a date, a group name, and observed vs expected data points. Can you run both a numeric distribution and a weighted mean analysis on the observed_points across these 150 rows so I can see where gaps are forming?"},{"title":"Dataset group coverage comparison","prompt":"I want to compare completeness across two dataset groups over the past quarter. Can you take my 90 rows of observed_points and expected_points data and give me a numeric distribution report plus a secondary-measure weighted mean, grouped by dataset_group?"},{"title":"Monitoring data quality for ETL feeds","prompt":"We track expected vs observed data points for each ETL feed daily. Can you run a numeric distribution and weighted mean analysis on the expected_points field for my 200-row completeness log so I can flag underperforming feeds?"}],"resultDescription":"Returns two analytical reports based on the supplied rows: (1) a numeric distribution summary for the selected field (observed_points or expected_points) across the dataset, and (2) a secondary-measure weighted mean. Both reports are computed locally against the provided data with no external lookups. Up to 200 rows processed per call.","failureModes":["Submitting more than 200 rows returns an error or truncated results","Missing required fields (row_id, date, observed_points, expected_points) cause validation failures","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Null values in both numeric fields may skew or invalidate weighted mean computation","Malformed JSON payload results in a 400-level error","Payment failure or insufficient USDC balance prevents the call from executing"],"whenToPreferThis":"Choose this endpoint when you have pre-collected time series completeness records with observed and expected point counts and need both a numeric distribution summary and a weighted mean in a single low-cost call ($0.01 USDC for two reports). It is ideal for offline or batch analytical workflows on up to 200 rows where no external data lookup, prediction, or real-time monitoring is needed — purely local computation on supplied data.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:57.439Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-distribution-secondary-measure-d9a69a16"}