{"uid":"cap_3nEKePP-kN8qa_MHORBB-","slug":"null-coverage-analytics-row-deduplication-iqr-outlier-flags-769b2d3c","name":"Null Coverage Analytics: Row Deduplication + IQR Outlier Flags","description":"Null coverage — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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-03-049?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_SAJSJGtrCp3zAWcVRaDWz","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":"Deduplicates exact rows and flags IQR-based outliers in null coverage data (missing_values, total_values) for up to 200 supplied records, returning 2 independent analytical reports.","exampleAgentPrompt":"I have a batch of up to 200 null coverage records with row IDs, dataset groups, dates, missing_values, and total_values — can you deduplicate the exact rows and flag any IQR outliers on the missing_values field, then give me 2 independent reports?","exampleUseCases":[{"title":"Data pipeline null coverage audit","prompt":"I've got 150 rows of null coverage data from our ETL pipeline — each has a row_id, dataset_group, date, missing_values, and total_values. Can you deduplicate any exact duplicate rows and flag which ones are IQR outliers on the missing_values field? I need 2 separate analytical reports."},{"title":"Detecting anomalous total_values across groups","prompt":"Here are 80 null coverage records across several dataset groups. Please deduplicate exact rows and run IQR outlier detection on the total_values field — I want to know which records are statistical anomalies."},{"title":"Pre-merge data quality check","prompt":"Before I merge these dataset quality logs, can you check for exact duplicate rows and flag any rows where missing_values is an IQR outlier? There are about 60 records, each with a row_id, group name, date, missing_values, and total_values."}],"resultDescription":"Returns 2 independent analytical reports: one identifying exact duplicate rows in the supplied dataset and one flagging rows whose selected field (missing_values or total_values) falls outside the interquartile range (IQR) bounds, all computed locally without external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds limit","Missing required fields (row_id, date, missing_values, total_values) — validation error","Date field in wrong format (not YYYY-MM-DD) — schema validation failure","Numeric values outside allowed range — schema rejection","All rows are unique with no outliers — reports returned but empty flagged sets"],"whenToPreferThis":"Choose this endpoint when you need fast, local statistical deduplication and IQR-based outlier detection specifically on null coverage metrics (missing_values, total_values) for up to 200 rows, and you do not need live lookups, predictions, or external data enrichment. It is ideal for data quality audits, pre-merge checks, or ETL pipeline validation where two independent reports (dedup + outlier) are needed in a single low-cost call.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T19:01:52.869Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-row-deduplication-iqr-outlier-flags-769b2d3c"}