{"uid":"cap_I4noKByT4RB-3MXYQOfDt","slug":"time-series-completeness-numeric-row-ordering-two-measure-correlation-f28e2dfb","name":"Time Series Completeness — Numeric Row Ordering + Two-Measure Correlation","description":"Time series completeness — Numeric row ordering + Two-measure correlation: Numeric row ordering + 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-16-120?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_6ptXaqE3IOFkwTwkOCE1i","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 numeric row ordering and two-measure correlation between observed_points and expected_points for up to 200 rows.","exampleAgentPrompt":"Can you run a numeric row ordering and two-measure correlation analysis on my time series completeness data? I have daily records from 2024-01-01 to 2024-01-10 for dataset groups 'sensors' and 'logs', each with observed_points and expected_points values — please analyze the observed_points field.","exampleUseCases":[{"title":"Data pipeline completeness audit","prompt":"I need to check whether my data pipeline is delivering the expected number of points each day. I have 30 days of records with observed_points and expected_points for two groups — can you run numeric row ordering and correlation analysis on the observed_points field to see how well actual delivery tracks expectations?"},{"title":"Multi-group dataset gap detection","prompt":"Can you analyze these completeness records for my 'web-events' and 'mobile-events' dataset groups? I have about 60 rows of daily observed_points and expected_points from last quarter — run the row ordering and two-measure correlation so I can see where the gaps are worst."},{"title":"Monthly reporting on sensor coverage","prompt":"I have 90 rows of daily sensor completeness data with observed_points and expected_points across three dataset groups. Can you compute the numeric row ordering and two-measure correlation on the expected_points field so I can include it in my monthly coverage report?"}],"resultDescription":"Returns two independent analytical reports for the supplied rows: (1) numeric row ordering of the selected field, and (2) two-measure correlation between observed_points and expected_points. All analysis is performed on the supplied data locally with no external lookups or predictions.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, date, dataset_group, observed_points, expected_points) — validation error","Date values not matching YYYY-MM-DD pattern — schema validation failure","Null values in both measures may reduce correlation reliability","Payment of 0.01 USDC not completed — request blocked by x402 paywall"],"whenToPreferThis":"Choose this endpoint when you need lightweight, on-demand statistical analysis of time series completeness data — specifically numeric row ordering combined with two-measure correlation — without needing a live data connection, external predictions, or professional assessment. Best for datasets of up to 200 rows where you want both ordering and correlation in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:42.753Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-numeric-row-ordering-two-measure-correlation-f28e2dfb"}