{"uid":"cap_q_U6pxMkPb8nreqC_mGzA","slug":"transformation-throughput-analytics-adjacent-row-changes-secondary-791a3d58","name":"Transformation Throughput Analytics — Adjacent Row Changes & Secondary-Measure Weighted Mean","description":"Transformation throughput — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean 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-13-159?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_hnJgWI91mbrfUu4X_x1v8","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-to-row changes and a secondary-measure weighted mean for transformation throughput records containing processed_rows and duration_seconds fields.","exampleAgentPrompt":"Can you run two analytical reports on my transformation throughput data — compute the adjacent row changes and the weighted mean of duration_seconds — for these pipeline runs: row-1 on 2026-10-01, group-a, 10 processed_rows, 1 duration_second; row-2 on 2026-10-02, group-b, 20 processed_rows, 2 duration_seconds; row-3 on 2026-10-03, group-a, 15 processed_rows, 3 duration_seconds?","exampleUseCases":[{"title":"ETL pipeline throughput trend review","prompt":"I have daily ETL run records with processed_rows and duration_seconds for each job — can you compute the adjacent row changes in processed_rows across those runs and also give me the weighted mean of duration_seconds, for up to 10 rows covering last week?"},{"title":"Dataset group performance comparison","prompt":"For my two dataset groups, group-a and group-b, I've got about 8 daily throughput records. Can you calculate how processed_rows changed between consecutive records and compute the duration_seconds weighted mean across all of them?"},{"title":"Pipeline regression detection after deployment","prompt":"After last week's deployment, I want to see if throughput dropped — can you analyze these 15 transformation records and show me the adjacent row changes in processed_rows plus the weighted mean of duration_seconds to spot any regression?"}],"resultDescription":"Two analytical reports derived from the supplied throughput records: (1) adjacent row-to-row changes for the specified field (processed_rows or duration_seconds), showing sequential deltas across up to 200 rows; and (2) a secondary-measure weighted mean, where one measure weights the average of the other. Results are computed locally with no external lookups or predictions.","failureModes":["Missing required fields (row_id, date, processed_rows, duration_seconds) cause validation errors","More than 200 rows submitted exceeds the max item limit","Invalid date format (not YYYY-MM-DD) rejected by schema pattern","Null values in processed_rows or duration_seconds may affect weighted mean computation","Invalid field enum value (not 'processed_rows' or 'duration_seconds') causes rejection","Insufficient USDC balance or payment failure blocks the call"],"whenToPreferThis":"Choose this endpoint when you need two specific statistical computations — adjacent sequential differences and a weighted mean — on transformation throughput tabular data (processed_rows, duration_seconds) in a single call. It is ideal for ETL pipeline analysis, batch throughput monitoring, and data engineering quality checks where you have up to 200 dated records and want local analytical results without external data enrichment or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:52.126Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-adjacent-row-changes-secondary-791a3d58"}