{"uid":"cap_BzKnoSq6LbmnDN8xdj_59","slug":"time-series-completeness-adjacent-row-changes-secondary-measure-59d42e51","name":"Time Series Completeness — Adjacent Row Changes + Secondary-Measure Weighted Mean","description":"Time series completeness — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean 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-16-159?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_f25unHkbNudJIZqTMl_D9","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 adjacent row-to-row changes and a secondary-measure weighted mean across up to 200 rows in two independent local reports.","exampleAgentPrompt":"Run the adjacent row changes and secondary-measure weighted mean reports on my time series completeness data — here are my rows with dates from 2026-10-01 to 2026-10-04, dataset groups 'group-a' and 'group-b', observed_points values of 10, 20, 15, 30 and expected_points of 1, 2, 3, 4. Use observed_points as the primary field.","exampleUseCases":[{"title":"Daily pipeline completeness drift check","prompt":"I have 30 days of completeness records for my ETL pipeline — each row has a date, a dataset group, observed_points, and expected_points. Can you run the adjacent row changes and weighted mean reports on these so I can see where my completeness drifted day over day? Use observed_points as the field."},{"title":"Dataset group weighted mean comparison","prompt":"Compare the secondary-measure weighted mean across my two dataset groups using these 50 completeness records — dates run from 2025-01-01 to 2025-02-19, with observed_points and expected_points per row. I want both the row change report and the weighted mean using expected_points as the field."},{"title":"Monitoring sensor coverage gaps","prompt":"I'm tracking sensor coverage completeness for 120 daily readings across three sensor groups. Can you produce the adjacent row changes report and the weighted mean summary for my observed_points column so I can see where gaps are clustering?"}],"resultDescription":"Returns two independent analytical reports computed locally: (1) an adjacent row changes report showing differences between consecutive rows for the selected field, and (2) a secondary-measure weighted mean report aggregating completeness metrics. No external data is fetched; analysis is based entirely on the supplied rows (up to 200).","failureModes":["Fewer than 1 row or more than 200 rows provided — request rejected","Invalid date format (not YYYY-MM-DD) causes row validation failure","Missing required fields (row_id, observed_points, expected_points) causes schema error","Null values in observed_points or expected_points may affect weighted mean calculation","Invalid field enum value (not 'observed_points' or 'expected_points') causes rejection"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous local analytical reports — adjacent row change attribution and a weighted mean — on time series completeness data (observed vs expected points) for up to 200 rows, without any live lookup or external data enrichment. It is ideal for lightweight, self-contained batch analysis of data pipeline or sensor completeness metrics at very low cost ($0.01 USDC).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:42:18.290Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-adjacent-row-changes-secondary-measure-59d42e51"}