{"uid":"cap_AkQKM0eICQSxjnDwNDrug","slug":"time-series-completeness-numeric-distribution-two-measure-correlation-10555b6c","name":"Time Series Completeness: Numeric Distribution + Two-Measure Correlation","description":"Time series completeness — Numeric distribution + Two-measure correlation: Numeric distribution + Two-measure correlation 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-16-081?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_g6fFDVT-5TH5VP_Ei129y","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":"Computes numeric distribution statistics and two-measure correlation for time series completeness records (observed_points vs expected_points) across up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you analyze the distribution and correlation between observed_points and expected_points for my time series completeness data? I have records for group-a and group-b across October 2026 — row-1 through row-4 — and want both a numeric distribution report and a two-measure correlation report.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I have daily counts of observed vs expected data points for two pipeline groups over the past month — can you run a numeric distribution and correlation analysis on these completeness records so I can see how well the pipelines are performing?"},{"title":"Sensor coverage gap analysis","prompt":"My sensor network logs expected readings and actual observed readings per day per region — run a distribution summary on the observed_points field and also show me how observed and expected counts correlate across my 150 rows of sensor data."},{"title":"Monitoring dashboard validation","prompt":"I need to validate my monitoring data — I have up to 200 rows with dataset groups, dates, observed_points, and expected_points. Can you give me both a numeric distribution breakdown and a two-measure correlation report so I can check if my expected and observed counts are tracking together?"}],"resultDescription":"Two independent analytical reports: (1) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram bins) for the selected field across the submitted rows, and (2) a two-measure correlation analysis between observed_points and expected_points across the dataset. Results are computed locally from the supplied data with no external lookups.","failureModes":["Missing required fields (row_id, date, observed_points, expected_points) returns a validation error","More than 200 rows submitted exceeds the maxItems limit and will be rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","All null values for the selected field may produce degenerate or empty distribution output","Payment of 0.01 USDC not provided or rejected causes HTTP 402 error"],"whenToPreferThis":"Choose this endpoint when you have pre-collected time series completeness records (observed vs expected data points) and need two types of quick statistical insight — numeric distribution and correlation — without requiring external lookups, predictions, or professional assessment. It is well-suited for data quality audits, pipeline monitoring, and batch completeness checks on up to 200 rows at very low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:38:34.227Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-distribution-two-measure-correlation-10555b6c"}