{"uid":"cap_8L33vs1AY1myt7Yl5f9-O","slug":"time-series-completeness-numeric-interval-filter-daily-sum-series-6e6c0bb5","name":"Time Series Completeness — Numeric Interval Filter + Daily Sum Series","description":"Time series completeness — Numeric interval filter + Daily sum series: Numeric interval filter + Daily sum 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-16-125?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_6QBAumffO3Z4pW9zUDMK5","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 and generates a daily sum series from observed/expected point data, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have completeness records for two dataset groups across several dates — each row has observed_points and expected_points. Can you filter by observed_points between 5 and 25, and also give me the daily sum series? Here are the rows: row-1 on 2026-10-01, group-a, expected=1, observed=10; row-2 on 2026-10-02, group-b, expected=2, observed=20; row-3 on 2026-10-03, group-a, expected=3, observed=15; row-4 on 2026-10-04, group-b, expected=4, observed=30.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I need to audit my pipeline's completeness records for October — I have up to 50 rows with observed_points and expected_points per day across two groups. Filter observed_points between 0 and 100 and give me the daily sum series so I can see where totals spike."},{"title":"Threshold breach investigation","prompt":"Can you check which of my completeness records have expected_points between 10 and 500? I have about 80 rows across dataset groups 'sensor-a' and 'sensor-b' with dates in November 2026 — and also give me the daily sum breakdown for expected_points."},{"title":"Multi-group daily aggregation report","prompt":"I have 120 time series completeness rows across four dataset groups for Q4 2026, each with observed and expected point counts. Run both the numeric interval filter (observed_points from 0 to 50) and the daily sum series on this data so I can see day-by-day totals alongside the filtered subset."}],"resultDescription":"Returns two analytical reports: (1) a numeric interval filter report listing records where the chosen field (observed_points or expected_points) falls within the specified minimum-maximum range, and (2) a daily sum series aggregating values by date. Both reports cover the supplied input rows (up to 200), computed using local analytical engines with no external data lookup.","failureModes":["More than 200 rows submitted — request is rejected with a validation error","Invalid date format (not YYYY-MM-DD) in any row causes a schema validation failure","Missing required row fields (row_id, date, observed_points, expected_points) causes rejection","Minimum value greater than maximum value may produce empty filter results or an error","Null values in observed_points or expected_points may be excluded from sum calculations"],"whenToPreferThis":"Choose this endpoint when you need two specific analytics on time series completeness data in a single low-cost call: a numeric interval filter and a daily sum aggregation. It is ideal for data quality monitoring workflows where you want to see both which records fall within a value range and how totals accumulate per day, without needing live lookups or predictive modeling. Best suited for batch completeness records up to 200 rows billed at a flat $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:54.766Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-interval-filter-daily-sum-series-6e6c0bb5"}