{"uid":"cap_YfC_yngUPgPP8pqU85hZ-","slug":"time-series-completeness-analytics-numeric-distribution-category-9e4f8a24","name":"Time Series Completeness Analytics — Numeric Distribution + Category Frequencies","description":"Time series completeness — Numeric distribution + Category frequencies: Numeric distribution + Category frequencies 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-16-072?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_tF1kYPuxtUa088FpWVSWx","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 up to 200 time series completeness records (observed vs expected data points) and returns two local analytical reports: a numeric distribution and category frequency breakdown.","exampleAgentPrompt":"Can you run a numeric distribution and category frequency analysis on my time series completeness data? I have up to 50 rows with fields like row_id, dataset_group, date, observed_points, and expected_points — analyze the observed_points field.","exampleUseCases":[{"title":"Pipeline completeness audit by group","prompt":"I have 120 rows of daily completeness records for my data pipelines — each row has a dataset_group, date, observed_points, and expected_points. Can you give me a numeric distribution and frequency breakdown of the observed_points field so I can see which groups are underperforming?"},{"title":"Sensor coverage gap analysis","prompt":"Here are 80 time series completeness records for our sensor network, with dates from last quarter and observed vs expected readings per group. Run a numeric distribution and category frequency report on expected_points so I can understand where our coverage targets were set."},{"title":"Monitoring dashboard stats for data quality team","prompt":"Our data quality team needs a quick statistical summary — I'll send you 150 completeness rows with dataset_group, date, observed_points, and expected_points. Please compute both a numeric distribution and the category frequencies across dataset groups for the observed_points field."}],"resultDescription":"Two analytical reports: (1) a numeric distribution of the selected field (observed_points or expected_points) across all submitted rows, showing spread, frequency, and statistical properties; (2) a category frequency table showing how often each dataset_group value appears in the provided records.","failureModes":["Missing required fields (row_id, date, observed_points, expected_points) causes validation failure","Submitting more than 200 rows exceeds the row limit and will be rejected","Invalid date format (not YYYY-MM-DD) causes schema validation error","Null values in the selected numeric field may affect distribution accuracy","Empty rows array returns an error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you have up to 200 time series completeness records and need both a numeric distribution and a category frequency report in a single API call for a flat $0.01 USDC fee. It is ideal for lightweight, offline analytical summarization of observed vs expected data point records without requiring any live data lookup, external integrations, or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:53.865Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-analytics-numeric-distribution-category-9e4f8a24"}