{"uid":"cap_vWmnCT4S2X6TLxJdyHszQ","slug":"time-series-completeness-adjacent-row-changes-keyed-dataset-comparison-e8a62bbc","name":"Time Series Completeness: Adjacent Row Changes + Keyed Dataset Comparison","description":"Time series completeness — Adjacent row changes + Keyed dataset comparison: Adjacent row changes + Keyed dataset comparison 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-16-161?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}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"expected_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_points":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_points":1,"observed_points":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_points":2,"observed_points":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_points","expected_points"],"type":"string","default":"observed_points"},"other":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","observed_points","expected_points"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","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":21},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_points":3,"observed_points":17},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_points":4,"observed_points":33}],"maxItems":200,"minItems":0}}},"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_RPLsAuxStfyQXgxuvOYnm","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 detecting adjacent row changes and comparing two keyed datasets, producing two independent analytical reports for up to 200 rows.","exampleAgentPrompt":"I have two sets of time series completeness records — each row has a date, row_id, dataset_group, observed_points, and expected_points — can you run adjacent row change detection and a keyed dataset comparison on them, analyzing the observed_points field, with up to 200 rows in each set?","exampleUseCases":[{"title":"Daily data pipeline completeness audit","prompt":"I have my pipeline's completeness log for the last 90 days — each row has a date, row_id, group name, observed_points, and expected_points. Can you run adjacent row change detection on the observed_points field and also compare it against last quarter's dataset using a keyed comparison?"},{"title":"Cross-version dataset discrepancy check","prompt":"I've got two versions of our completeness dataset — version A and version B — both with row_id, date, dataset_group, observed_points, and expected_points. Run a keyed comparison between them and also show me the adjacent row changes in observed_points so I can see what shifted between versions."},{"title":"QA validation for sensor data completeness","prompt":"Our sensor monitoring system exports daily completeness records with observed vs expected data points per group. Can you analyze adjacent row changes and do a keyed dataset comparison between this week's export and last week's, analyzing the observed_points field across up to 150 rows?"}],"resultDescription":"Returns two independent analytical reports: (1) an adjacent row changes report showing how the selected field (observed_points or expected_points) shifts between consecutive rows, and (2) a keyed dataset comparison report highlighting differences between the primary rows dataset and the supplied comparison dataset, keyed by row_id and dataset_group. All analysis is performed locally on supplied data with no external lookups.","failureModes":["Fewer than 1 row supplied — minItems validation error","More than 200 rows supplied — maxItems validation error","Missing required fields (row_id, dataset_group, date, observed_points, expected_points) — schema validation error","Invalid date format (not YYYY-MM-DD) — pattern validation error","row_id exceeds 80 characters — maxLength validation error","Numeric values outside ±1,000,000,000,000 range — bounds validation error","Payment not processed or insufficient USDC balance — x402 payment failure"],"whenToPreferThis":"Choose this endpoint when you need both adjacent row change detection and a keyed dataset comparison on time series completeness data (observed vs expected points) in a single $0.01 call. Ideal for data quality pipelines that track sensor completeness, ETL pipeline output validation, or version-to-version dataset diffing — all without requiring any external data sources or live lookups. Prefer over single-report endpoints when you want both analyses bundled cost-effectively.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:42:07.256Z","isFirstParty":false,"canonicalSlug":"time-series-completeness-adjacent-row-changes-keyed-dataset-comparison-e8a62bbc"}