{"uid":"cap_HSHOgAjavYeqJIrPcAT-Y","slug":"transformation-throughput-analytics-numeric-distribution-date-by-0162050b","name":"Transformation Throughput Analytics: Numeric Distribution + Date-by-Category Pivot","description":"Transformation throughput — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot 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-13-083?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_7y9RkmCFcRGK65Q6PDZ7Q","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":"Generates two local analytical reports — a numeric distribution and a date-by-category pivot — for transformation throughput records containing processed_rows and duration_seconds fields.","exampleAgentPrompt":"I have a batch of ETL run records — up to 200 rows each with a row_id, dataset_group, date, processed_rows, and duration_seconds — can you give me both a numeric distribution and a date-by-category pivot on the processed_rows field?","exampleUseCases":[{"title":"ETL pipeline throughput distribution review","prompt":"I have 150 transformation job records with dataset groups like 'sales' and 'inventory', dates in October 2026, and processed_row counts — can you run a numeric distribution and a date-by-category pivot on processed_rows so I can see how throughput is spread across groups over time?"},{"title":"Duration bottleneck analysis by group","prompt":"Here are my pipeline run logs for the past month — each record has a row_id, dataset_group, date, processed_rows, and duration_seconds. Can you generate a numeric distribution and date-by-category pivot focused on duration_seconds so I can spot which groups are slowest?"},{"title":"Daily throughput pattern summary for data team","prompt":"I've collected 80 transformation records from our nightly jobs across three dataset groups over the last quarter. Run me a numeric distribution and a date-by-category pivot on processed_rows so the data team can see daily throughput patterns by group."}],"resultDescription":"Two analytical reports: (1) a numeric distribution report showing statistical spread (e.g. min, max, mean, percentiles, histogram buckets) for the selected field (processed_rows or duration_seconds), and (2) a date-by-category pivot table aggregating the selected field values grouped by dataset_group across dates — all computed locally from the supplied rows with no external data lookup.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) — schema validation error","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Null values in the selected numeric field may reduce distribution accuracy","Payment not confirmed — endpoint returns 402 before processing"],"whenToPreferThis":"Choose this endpoint when you have up to 200 transformation throughput records and need both a numeric distribution and a date-by-category pivot in a single low-cost call ($0.01 USDC). Ideal for data engineers who want quick statistical summaries and temporal group breakdowns of ETL job metrics (processed_rows or duration_seconds) without needing live data lookup, ML prediction, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:42:02.301Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-numeric-distribution-date-by-0162050b"}