{"uid":"cap_sZpwmMawaCubEqQIvymoI","slug":"time-series-completeness-numeric-row-ordering-date-by-category-pivot-6571ec59","name":"Time Series Completeness — Numeric Row Ordering + Date by Category Pivot","description":"Time series completeness — Numeric row ordering + Date by category pivot: Numeric row ordering + Date by category pivot 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-16-122?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_bHWr0I0O-AJn-vFbNaCig","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 data by producing two local analytical reports: numeric row ordering and a date-by-category pivot table, for up to 200 rows of observed vs. expected data points.","exampleAgentPrompt":"I have daily time series completeness records for two groups — 'group-a' and 'group-b' — with dates from 2026-10-01 to 2026-10-04 and both observed_points and expected_points values. Can you run the numeric row ordering and date-by-category pivot reports on observed_points for all 4 rows?","exampleUseCases":[{"title":"Auditing sensor data completeness by site","prompt":"I have 150 rows of daily sensor readings for multiple site groups with observed and expected data point counts. Can you give me a numeric row ordering and a date-by-category pivot on observed_points so I can see where each site is missing data?"},{"title":"Monitoring ETL pipeline output gaps","prompt":"Our ETL pipeline produces daily records across three pipeline groups — I want to check completeness using the numeric ordering and date-pivot reports on expected_points for the last 90 days of records I'm supplying."},{"title":"Quarterly data coverage review by product line","prompt":"I need to review time series completeness for four product lines across Q3 — I have 200 rows of observed vs expected data points by date and group. Run the numeric row ordering and date-by-category pivot reports on observed_points for me."}],"resultDescription":"Returns two analytical reports computed locally on the supplied data: (1) a numeric row ordering of the time series completeness records, and (2) a date-by-category pivot table showing the selected field (observed_points or expected_points) broken down by dataset_group across dates. No external data is fetched or predicted.","failureModes":["Fewer than 1 row or more than 200 rows supplied — request rejected","Invalid date format (not YYYY-MM-DD) causes validation error","Missing required fields (row_id, dataset_group, date, observed_points, expected_points) cause schema rejection","Invalid field enum value (not 'observed_points' or 'expected_points') causes error","Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) rejected"],"whenToPreferThis":"Choose this endpoint when you have pre-collected time series completeness records (observed vs. expected data points) and need two structured local analytics reports — numeric row ordering and a date-by-category pivot — without requiring any live data lookup, external enrichment, or prediction. Ideal for data quality audits, ETL monitoring, or completeness dashboards where the data is already in hand and you want fast, low-cost ($0.01) dual-report output on up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:42:09.386Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-row-ordering-date-by-category-pivot-6571ec59"}