{"uid":"cap_wlHuamQ7U5zD0SC3eVRwI","slug":"data-validation-results-explicit-missing-value-fill-a1b95a70","name":"Data Validation Results – Explicit Missing-Value Fill","description":"Data validation results - Explicit missing-value fill: Explicit missing-value fill 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 explicit missing-value fill report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-validation-results-fill-missing?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_QZ8nZi5kFH80BnjAcLFwv","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":"Fills missing numeric values in data validation result records (checked_records or failed_records) using a chosen imputation method (zero, mean, or median).","exampleAgentPrompt":"I have up to 200 rows of data validation results with some null checked_records values — can you fill those missing values using median imputation across my rule-grouped date series?","exampleUseCases":[{"title":"QA pipeline null remediation","prompt":"My data validation pipeline produced a week's worth of rule-level results but several checked_records entries came back null — fill those missing values using median imputation so I can run my downstream quality report."},{"title":"Zero-fill for failed record gaps","prompt":"I have about 150 rows of daily validation results across two rule groups and some of the failed_records fields are missing — fill them with zeros so I can calculate my overall failure rate."},{"title":"Mean imputation for audit preparation","prompt":"Before our compliance audit, I need to patch the gaps in our validation result dataset — please impute the missing checked_records values using the mean method across these 80 rows."}],"resultDescription":"Returns the submitted validation result rows with missing values in the specified field (checked_records or failed_records) replaced according to the chosen imputation method (zero, mean, or median), along with a bounded descriptive analytics report. No external enrichment or forecasting is performed.","failureModes":["Rows array empty or missing — returns validation error","Row missing required fields (row_id, rule, date, checked_records, failed_records) — returns schema error","More than 200 rows submitted — exceeds maxItems limit, returns error","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Invalid method or field enum value — returns schema validation error","Payment not fulfilled — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you have tabular validation result records (up to 200 rows) with null numeric fields and need a fast, local imputation (zero, mean, or median) without any external enrichment, ML models, or forecasting. Ideal for lightweight data cleaning steps in QA pipelines or audit preparation workflows where a simple statistical fill suffices.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T19:04:23.932Z","isFirstParty":false,"canonicalSlug":"data-validation-results-explicit-missing-value-fill-a1b95a70"}