{"uid":"cap_kdtBeHGtjDr6KKzwm9fr_","slug":"null-coverage-iqr-outlier-flags-date-by-category-pivot-3455f90e","name":"Null Coverage IQR Outlier Flags + Date-by-Category Pivot","description":"Null coverage — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot for supplied null coverage records (missing_values, total_values). 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-03-178?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"}}},"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_y6N-8W3tVLXDsJoMBRijB","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":"Analyzes up to 200 null-coverage records (missing_values, total_values) and returns two local analytical reports: IQR-based outlier flags and a date-by-category pivot table.","exampleAgentPrompt":"I have 150 null-coverage records with row_id, dataset_group, date, missing_values, and total_values — can you run IQR outlier flagging and a date-by-category pivot on the missing_values field for all of them?","exampleUseCases":[{"title":"Outlier detection in ETL pipeline audits","prompt":"I have audit records from my ETL jobs — each row has a dataset group, a date, and counts of missing vs total values. Can you flag which rows have outlier missing_values using IQR and also give me a pivot of missing_values by date and group?"},{"title":"Monthly data quality review across teams","prompt":"Here are 120 null-coverage records from our three data teams for October 2026, each tagged with a dataset_group and date. Run the IQR outlier flags plus the date-by-category pivot on total_values so I can see which groups had unusual completeness numbers."},{"title":"Pre-release dataset validation report","prompt":"Before we ship this dataset, I need two reports on our null coverage stats — IQR-based outlier flags on missing_values and a date-by-category breakdown — here are the 80 rows with row_id, date, dataset_group, missing_values, and total_values."}],"resultDescription":"Returns two analytical reports: (1) IQR outlier flags for each row indicating whether the selected field (missing_values or total_values) is an outlier based on interquartile range thresholds, and (2) a pivot table summarizing the selected field's values grouped by date and dataset_group category. All computation is performed locally with no external lookups.","failureModes":["Fewer than 1 row submitted — minItems:1 violation returns validation error","More than 200 rows submitted — maxItems:200 limit exceeded","Invalid date format (not YYYY-MM-DD pattern) causes schema validation failure","Non-numeric or out-of-range missing_values or total_values rejected by schema","Missing required fields (row_id, dataset_group, date) cause per-row validation errors","Insufficient row variance for meaningful IQR calculation with very small datasets","Payment failure or insufficient USDC balance blocks request"],"whenToPreferThis":"Choose this endpoint when you have up to 200 null-coverage or data-completeness records and need both IQR-based outlier detection and a date-by-category pivot in a single low-cost call ($0.01 USDC). Ideal for data quality monitoring workflows, ETL audit reporting, or pre-release dataset validation where no external data enrichment or live lookup is needed — just fast, local analytical computation on your supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:22.241Z","isFirstParty":false,"canonicalSlug":"null-coverage-iqr-outlier-flags-date-by-category-pivot-3455f90e"}