{"uid":"cap_azPaiPZP4zmpBgAqr1eVR","slug":"transformation-throughput-analytics-adjacent-row-changes-two-measure-f98b1464","name":"Transformation Throughput Analytics — Adjacent Row Changes + Two-Measure Correlation","description":"Transformation throughput — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied transformation throughput records (processed_rows, duration_seconds). 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-13-158?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"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},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_rows"}}},"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_85Uu3zW0plnC04bdZtXp7","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":"Computes adjacent row changes and two-measure correlation for transformation throughput records (processed_rows, duration_seconds) on up to 200 supplied rows, returning two analytical reports.","exampleAgentPrompt":"Can you analyze my transformation throughput records for adjacent row changes and compute the correlation between processed_rows and duration_seconds? I have 4 records: 2026-10-01 group-a 10 rows in 1s, 2026-10-02 group-b 20 rows in 2s, 2026-10-03 group-a 15 rows in 3s, 2026-10-04 group-b 30 rows in 4s — use processed_rows as the primary field.","exampleUseCases":[{"title":"ETL batch run throughput drift detection","prompt":"I've got 50 daily ETL batch records with processed_rows and duration_seconds — can you compute the adjacent row changes for processed_rows so I can see how my throughput is shifting day over day, and also check the correlation between processed_rows and duration_seconds?"},{"title":"Pipeline scaling linearity check","prompt":"I want to know if my data pipeline scales linearly — can you take my 120 records with processed_rows and duration_seconds and run a two-measure correlation plus show me how adjacent records differ in processed_rows?"},{"title":"Multi-group throughput comparison","prompt":"I have transformation throughput logs for two dataset groups across 80 records — please analyze the adjacent row changes in duration_seconds and show me the correlation between processed_rows and duration_seconds across all entries."}],"resultDescription":"Returns two analytical reports: (1) an adjacent row changes report showing sequential differences between consecutive records for the selected field (processed_rows or duration_seconds), and (2) a two-measure correlation report quantifying the statistical relationship between processed_rows and duration_seconds across all supplied rows. No external data is fetched; analysis is performed entirely on the supplied records.","failureModes":["Fewer than 1 row supplied — minimum row count not met","More than 200 rows supplied — exceeds maximum row limit","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Missing required fields (row_id, processed_rows, duration_seconds) causes rejection","Null values in both measures may produce undefined correlation result","Invalid field enum value (not 'processed_rows' or 'duration_seconds') causes error","Payment of 0.01 USDC not completed — request blocked by x402 paywall"],"whenToPreferThis":"Choose this endpoint when you need both sequential/adjacent-row change analysis and a two-measure correlation between processed_rows and duration_seconds in a single paid call, using only your supplied data (no external lookups). It is well-suited for ETL pipeline monitoring, batch processing diagnostics, and throughput scaling analysis on up to 200 records. Prefer this over single-report endpoints when you need both analytical outputs bundled at $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:59.119Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-adjacent-row-changes-two-measure-f98b1464"}