{"uid":"cap_wGxAm6jo03rMTyxfV4B_F","slug":"data-pipeline-runs-date-by-category-pivot-d7bdaead","name":"Data Pipeline Runs – Date by Category Pivot","description":"Data pipeline runs - Date by category pivot: Date by category pivot for Data pipeline runs. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded date by category pivot report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-pipeline-runs-pivot?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","pipeline","date","processed_rows","rejected_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"pipeline":{"type":"string","default":"","maxLength":80},"rejected_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","pipeline":"group-a","rejected_rows":1,"processed_rows":10},{"date":"2026-10-02","row_id":"row-2","pipeline":"group-b","rejected_rows":2,"processed_rows":20},{"date":"2026-10-03","row_id":"row-3","pipeline":"group-a","rejected_rows":3,"processed_rows":15},{"date":"2026-10-04","row_id":"row-4","pipeline":"group-b","rejected_rows":4,"processed_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","rejected_rows"],"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_QyaIkixNenhMDWn9p1d8x","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 a date-by-category pivot table for data pipeline run metrics (processed rows or rejected rows) across up to 200 supplied records.","exampleAgentPrompt":"Pivot my pipeline run data by date and pipeline category — I have records for pipelines 'ingest' and 'transform' across the past week, up to 50 rows total, and I want to see processed_rows broken down by each pipeline per day.","exampleUseCases":[{"title":"Daily rejected-row breakdown by pipeline","prompt":"I have 120 pipeline run records from last month for pipelines 'sales-etl' and 'inventory-etl' and I want a pivot table showing rejected_rows by date for each pipeline — can you build that for me?"},{"title":"Weekly processed-row comparison across teams","prompt":"Can you cross-tab my pipeline run data showing processed_rows by date and pipeline group? I've got records for pipelines 'team-alpha', 'team-beta', and 'team-gamma' across the last two weeks, about 80 rows."},{"title":"Data quality audit pivot for QA review","prompt":"I need a date-by-category pivot of rejected_rows for our QA audit — here are 45 pipeline run records across pipelines 'raw-loader' and 'cleaner', show me which pipeline had the most rejections on each day."}],"resultDescription":"Returns a pivot table where rows represent dates and columns represent pipeline category names, with each cell containing the aggregated value of the chosen metric field (processed_rows or rejected_rows). Covers up to 200 input records and provides local descriptive analytics with no enrichment or forecasting.","failureModes":["Input array is empty or missing (minItems: 1 violation)","Input exceeds 200 records (maxItems: 200 violation)","Invalid date format — must match YYYY-MM-DD pattern","Unknown field value — must be 'processed_rows' or 'rejected_rows'","Numeric values out of allowed range (±1,000,000,000,000)","Missing required fields: row_id, pipeline, date, processed_rows, or rejected_rows","Payment not received or insufficient USDC balance"],"whenToPreferThis":"Choose this endpoint when you have pipeline run records with date and category (pipeline name) dimensions and need a quick local pivot table for descriptive analytics — no external data enrichment, forecasting, or ML is required. Ideal for operational dashboards, QA audits, or ad-hoc pipeline performance reviews where data stays local and results are needed fast at minimal cost ($0.01 USDC).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T00:52:35.239Z","isFirstParty":false,"canonicalSlug":"data-pipeline-runs-date-by-category-pivot-d7bdaead"}