{"uid":"cap_St768wkN00H-s35UvSKA9","slug":"time-series-completeness-duplicate-key-report-two-measure-correlation-13e618f1","name":"Time Series Completeness — Duplicate Key Report + Two-Measure Correlation","description":"Time series completeness — Duplicate key report + Two-measure correlation: Duplicate key report + 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-16-066?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}}},"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_ryYab7PMf3B2Qhw7J33Xt","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 rows of time series completeness records to produce a duplicate key report and a two-measure correlation analysis between observed_points and expected_points.","exampleAgentPrompt":"Can you run a duplicate key report and a correlation analysis between observed_points and expected_points on my time series completeness records? I have rows like: row-1 for group-a on 2026-10-01 with 10 observed and 1 expected, row-2 for group-b on 2026-10-02 with 20 observed and 2 expected, and so on up to about 50 rows.","exampleUseCases":[{"title":"Duplicate detection in completeness logs","prompt":"I have a batch of daily completeness records for two dataset groups — can you check if there are any duplicate row IDs or date/group combinations in this data? Here are 80 rows with row_id, dataset_group, date, observed_points, and expected_points fields."},{"title":"Observed vs expected correlation check","prompt":"I want to know how strongly my observed_points correlate with my expected_points across 150 daily completeness records — can you run a two-measure correlation report on this data and tell me if they move together?"},{"title":"Data quality audit before pipeline ingestion","prompt":"Before I ingest these 120 time series completeness rows into our pipeline, can you give me a duplicate key report and a correlation analysis between the observed and expected point counts so I can catch any data quality issues?"}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any rows sharing the same key combinations (e.g., duplicate row_id, date, or dataset_group), and (2) a two-measure correlation report quantifying the statistical relationship between observed_points and expected_points across the supplied rows. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows causes rejection — trim input to at most 200 items","Missing required fields (row_id, date, observed_points, expected_points) cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern will fail schema validation","Supplying fewer than 1 row causes an error","Null values in observed_points or expected_points may reduce correlation quality or produce warnings"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of time series completeness data (with observed and expected point counts) and need both a duplicate key audit and a correlation analysis in a single, low-cost call ($0.01 USDC). Prefer it over general-purpose analytics tools when you want a self-contained, offline computation with no external data lookups, and when your data already conforms to the row_id/dataset_group/date/observed_points/expected_points schema.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:39:03.330Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-duplicate-key-report-two-measure-correlation-13e618f1"}