{"uid":"cap_8W7KKDMW302yc8npNMPa0","slug":"time-series-completeness-exact-row-deduplication-two-measure-9502e999","name":"Time Series Completeness — Exact Row Deduplication + Two-Measure Correlation","description":"Time series completeness — Exact row deduplication + Two-measure correlation: Exact row deduplication + 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-16-050?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_WhMrgu98fd7YvF_vDXi5m","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":"Deduplicates exact rows and computes two-measure correlation for time series completeness records (observed_points vs expected_points) across up to 200 rows.","exampleAgentPrompt":"I have a batch of time series completeness records with row IDs, dataset groups, dates, observed_points, and expected_points — up to 200 rows — can you deduplicate exact rows and also compute the correlation between observed and expected points across those records?","exampleUseCases":[{"title":"Daily pipeline completeness audit","prompt":"I'm tracking data pipeline completeness for two dataset groups over the past month — each row has a date, a row_id, a dataset_group, plus observed_points and expected_points. Can you strip out any exact duplicate rows and tell me how correlated observed and expected points are?"},{"title":"Sensor data coverage check","prompt":"I've got up to 180 rows of sensor coverage records, each with a date, row_id, dataset_group, observed_points, and expected_points. Can you find any perfectly duplicated rows and compute the two-measure correlation between observed and expected point counts?"},{"title":"Ingestion monitoring report","prompt":"Here are our ingestion completeness logs — dates range from 2025-01-01 to 2025-06-30, grouped by dataset_group, with observed_points and expected_points per day. Please deduplicate exact rows and give me the correlation between those two measures."}],"resultDescription":"Returns two analytical reports: (1) an exact row deduplication report identifying and removing fully duplicate rows from the supplied dataset, and (2) a two-measure correlation report quantifying the statistical relationship between observed_points and expected_points across the deduplicated time series records. Both reports are computed locally without external lookups or predictions.","failureModes":["Exceeding 200 rows causes rejection","Missing required fields (row_id, date, observed_points, expected_points) causes validation failure","Malformed date strings not matching YYYY-MM-DD pattern are rejected","All rows being duplicates may yield an empty deduplicated set","Null values in observed_points or expected_points may affect correlation computation","Insufficient variance in either measure may produce undefined or unreliable correlation"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously clean a time series completeness dataset of exact duplicate rows AND measure the linear relationship between observed and expected data points, all in a single low-cost call. It is ideal for datasets up to 200 rows where no live external data, predictions, or professional assessments are needed — just local statistical computation on supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:42:32.933Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-exact-row-deduplication-two-measure-9502e999"}