{"uid":"cap_WCLV4chcHmA1Hp0s2nQTl","slug":"time-series-completeness-category-frequencies-date-by-category-pivot-026339f6","name":"Time Series Completeness — Category Frequencies + Date by Category Pivot","description":"Time series completeness — Category frequencies + Date by category pivot: Category frequencies + 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-16-110?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_XxZ6ux0H5_Elu7H-EGGeq","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 computing category frequencies and a date-by-category pivot table for observed vs. expected data points.","exampleAgentPrompt":"Can you run a completeness analysis on my time series data — I have observed_points and expected_points for groups 'group-a' and 'group-b' across dates 2026-10-01 to 2026-10-04, and I want both a category frequency breakdown and a date-by-category pivot table for the observed_points field?","exampleUseCases":[{"title":"IoT sensor coverage audit","prompt":"I have daily sensor readings for three device groups — alpha, beta, and gamma — from 2025-01-01 to 2025-03-31, with observed_points and expected_points for each day. Can you give me a category frequency report and a date-by-group pivot so I can see which groups are consistently under-reporting?"},{"title":"ETL pipeline completeness check","prompt":"My ETL pipeline tracks expected vs actual data points loaded each day across pipelines 'crm-sync', 'inventory-feed', and 'orders-feed' for the past two weeks. Can you pivot those completeness records by date and pipeline and also show me the frequency breakdown by pipeline?"},{"title":"Multi-dataset monitoring summary","prompt":"I've got time series completeness data for four dataset groups over the last month — each row has a date, group name, observed_points, and expected_points. I want a category frequency table showing how often each group appears, plus a date-by-category pivot for the expected_points field, so I can spot any gaps."}],"resultDescription":"Returns two analytical reports: (1) a category frequencies table showing how often each dataset_group appears in the supplied records, and (2) a date-by-category pivot table showing the selected field (observed_points or expected_points) broken down by date and dataset_group — all computed locally on the supplied data, up to 200 rows.","failureModes":["Missing required fields (row_id, dataset_group, date, observed_points, expected_points) cause validation errors","Date values not matching YYYY-MM-DD pattern are rejected","Submitting more than 200 rows exceeds the row limit and returns an error","Null values in observed_points or expected_points may result in gaps in pivot output","Empty rows array returns an error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you have tabular time series completeness data (observed vs. expected points) segmented by category/group and date, and need both a frequency distribution of categories and a date-by-category pivot in a single low-cost call. Ideal for lightweight, offline analytical summarization of up to 200 rows without needing an external BI tool or database.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:05.990Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-category-frequencies-date-by-category-pivot-026339f6"}