{"uid":"cap_jXZ0zvtIj2VTJgUkDWyXc","slug":"data-validation-results-date-by-category-pivot-e64be0b4","name":"Data Validation Results – Date by Category Pivot","description":"Data validation results - Date by category pivot: Date by category pivot for Data validation results. 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-validation-results-pivot?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","rule","date","checked_records","failed_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"rule":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"failed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","rule":"group-a","row_id":"row-1","failed_records":1,"checked_records":10},{"date":"2026-10-02","rule":"group-b","row_id":"row-2","failed_records":2,"checked_records":20},{"date":"2026-10-03","rule":"group-a","row_id":"row-3","failed_records":3,"checked_records":15},{"date":"2026-10-04","rule":"group-b","row_id":"row-4","failed_records":4,"checked_records":30}],"maxItems":200,"minItems":1},"field":{"enum":["checked_records","failed_records"],"type":"string","default":"checked_records"}}},"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_f_YRDd7LMIfI3aWbEsFma","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":"Pivots data validation results (checked and failed records) by date and rule category, producing a cross-tabulated summary report for up to 200 input rows.","exampleAgentPrompt":"Can you pivot my data validation results by date and rule category? I have records with dates, rule names like 'null-check' and 'range-check', plus checked_records and failed_records counts — I want to see the failed_records broken down in a date-by-category table.","exampleUseCases":[{"title":"Daily data quality rule breakdown","prompt":"I have validation logs from last week with columns for date, rule name, checked records, and failed records — can you pivot them by date and rule category so I can see which rules are failing most on which days?"},{"title":"Monitoring pipeline validation failures","prompt":"My ETL pipeline runs daily validation checks across multiple rules. Here are 150 rows of results with dates, rule names, and failure counts — give me a pivot table showing failed_records by date and rule so I can spot problem areas."},{"title":"Data governance audit summary","prompt":"I need to prepare a data governance report. Can you take these 80 validation result records — each with a date, a category like 'schema-check' or 'referential-integrity', and counts of checked and failed records — and produce a date-by-category pivot on failed_records?"}],"resultDescription":"A pivot table report where rows represent dates and columns represent rule/category names, with each cell containing the aggregated value of the selected field (checked_records or failed_records). Covers up to 200 input rows with purely local descriptive analytics — no enrichment or forecasting.","failureModes":["Input array is empty or missing (minItems:1 violation)","Input exceeds 200 rows (maxItems:200 violation)","Date fields do not match required YYYY-MM-DD pattern","row_id missing or empty string (minLength:1 violation)","Numeric fields out of allowed range (±1,000,000,000,000)","Invalid field enum value (must be 'checked_records' or 'failed_records')","Payment of 0.01 USDC not fulfilled — 402 Payment Required response"],"whenToPreferThis":"Choose this endpoint when you have tabular data validation results with date and rule/category dimensions and need a quick local pivot summary without any external enrichment, forecasting, or machine learning. It is ideal for data quality dashboards, pipeline monitoring, and governance reporting workflows where a cross-tab of failures by date and rule is the required output format. Best suited for batch sizes up to 200 rows at very low cost ($0.01 per call).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-21T00:52:36.567Z","isFirstParty":false,"canonicalSlug":"data-validation-results-date-by-category-pivot-e64be0b4"}