{"uid":"cap_rdG-YnuwIRPpBMsD-Np0b","slug":"transformation-throughput-numeric-interval-filter-daily-sum-series-8880b2c3","name":"Transformation Throughput — Numeric Interval Filter + Daily Sum Series","description":"Transformation throughput — Numeric interval filter + Daily sum series: Numeric interval filter + Daily sum series 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-13-125?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_V1zpGIr0NiQq2BDMVNHIk","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":"Filters transformation throughput records (processed_rows, duration_seconds) by a numeric interval and generates a daily sum time series from the supplied data.","exampleAgentPrompt":"Filter my transformation throughput records where processed_rows is between 10 and 500, then give me the daily sum series — here's the data: row-1 on 2026-10-01 group-a processed_rows=10 duration_seconds=1, row-2 on 2026-10-02 group-b processed_rows=300 duration_seconds=2, row-3 on 2026-10-03 group-a processed_rows=600 duration_seconds=3.","exampleUseCases":[{"title":"Daily ETL row throughput anomaly check","prompt":"I have 50 rows of ETL job logs with date, processed_rows, and duration_seconds for last month — can you filter to only records where processed_rows is between 0 and 1000 and show me the total processed rows summed by day?"},{"title":"Pipeline duration daily totals by interval","prompt":"Filter my pipeline records for duration_seconds between 5 and 120 seconds, then give me a daily sum series so I can see which days had the most total processing time — I'll paste the records now."},{"title":"Dataset group throughput trend review","prompt":"I want to analyze transformation throughput for groups A and B over the past two weeks — filter where processed_rows is between 50 and 500 and aggregate into a daily total series so I can spot trends."}],"resultDescription":"Two reports: (1) the subset of supplied rows where the chosen field (processed_rows or duration_seconds) falls within the specified [minimum, maximum] interval, and (2) a daily sum time series aggregating the chosen field by date across all supplied rows. Up to 200 input rows supported.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required row fields (row_id, date, processed_rows, duration_seconds) — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure","Minimum greater than maximum — may produce empty filter result","field enum value not recognized — schema validation error","Empty rows array — rejected by minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you have up to 200 transformation throughput records (with processed_rows and/or duration_seconds fields) and need both a numeric interval filter AND a daily sum aggregation in a single call. It is purpose-built for ETL/pipeline throughput analysis on supplied data without any external lookups or live data connections. Cost-effective at $0.01 for two bundled reports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:49.845Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-numeric-interval-filter-daily-sum-series-8880b2c3"}