{"uid":"cap_g1QkdiCxiHMWOiUtahobQ","slug":"time-series-completeness-numeric-interval-filter-secondary-measure-85885c4a","name":"Time Series Completeness — Numeric Interval Filter + Secondary-Measure Weighted Mean","description":"Time series completeness — Numeric interval filter + Secondary-measure weighted mean: Numeric interval filter + 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-16-132?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_tZQAq_hxtXkFPoYRmQq0b","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":"Filters time series completeness records by a numeric interval on one measure, then computes a secondary-measure weighted mean across the filtered rows — returning two analytical reports for up to 200 supplied rows.","exampleAgentPrompt":"I have 4 completeness records — row-1 (group-a, 2026-10-01, observed=10, expected=1), row-2 (group-b, 2026-10-02, observed=20, expected=2), row-3 (group-a, 2026-10-03, observed=15, expected=3), row-4 (group-b, 2026-10-04, observed=30, expected=4) — filter them where observed_points is between 0 and 20, then give me the weighted mean using expected_points as the secondary measure.","exampleUseCases":[{"title":"Data pipeline completeness QA","prompt":"I have daily completeness logs for two dataset groups across last week — observed_points and expected_points per day — can you filter to only the rows where observed_points falls between 5 and 25, then compute the weighted mean of expected_points across that filtered set and give me both reports?"},{"title":"Anomalous completeness range investigation","prompt":"Here are 50 completeness records for my sensor datasets with observed and expected point counts per day; filter out any row where expected_points is outside the range 10 to 500, then calculate the weighted mean of observed_points for the ones that remain."},{"title":"Group-level completeness summary","prompt":"I've got completeness data for group-a and group-b spanning 3 months — up to 200 rows total — please filter where observed_points is between 0 and 100, then give me a weighted mean using expected_points as the weight measure, split into the two analytical reports."}],"resultDescription":"Returns two analytical reports derived from the supplied completeness rows: (1) rows filtered to those where the selected field (observed_points or expected_points) falls within the specified numeric interval [minimum, maximum], and (2) a secondary-measure weighted mean computed across those filtered rows. Reports are generated locally from supplied data with no external lookups.","failureModes":["Fewer than 1 or more than 200 rows supplied — request rejected","date values not matching YYYY-MM-DD pattern — validation error","minimum greater than maximum — undefined or empty filter result","null values in observed_points or expected_points affecting weighted mean calculation","row_id missing or exceeding 80 characters — schema validation failure","field enum value not one of 'observed_points' or 'expected_points' — rejected"],"whenToPreferThis":"Choose this endpoint when you have pre-collected time series completeness records (observed vs expected point counts) and need both an interval-filtered subset and a weighted mean computed locally from your supplied data — no external data fetch, prediction, or live lookup required. Ideal for data quality audits, pipeline monitoring summaries, and batch completeness analytics on up to 200 rows at low cost ($0.01 USDC for 2 reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:49.844Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-interval-filter-secondary-measure-85885c4a"}