{"uid":"cap_UnNHmRgW9Ib4qCkqpr4fR","slug":"duplicate-observations-analytics-numeric-row-ordering-iqr-outlier-flags-11df0fba","name":"Duplicate Observations Analytics — Numeric Row Ordering + IQR Outlier Flags","description":"Duplicate observations — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied duplicate observations records (duplicate_rows, total_rows). 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-04-119?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","duplicate_rows","total_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"duplicate_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_rows":1,"dataset_group":"group-a","duplicate_rows":10},{"date":"2026-10-02","row_id":"row-2","total_rows":2,"dataset_group":"group-b","duplicate_rows":20},{"date":"2026-10-03","row_id":"row-3","total_rows":3,"dataset_group":"group-a","duplicate_rows":15},{"date":"2026-10-04","row_id":"row-4","total_rows":4,"dataset_group":"group-b","duplicate_rows":30}],"maxItems":200,"minItems":1},"field":{"enum":["duplicate_rows","total_rows"],"type":"string","default":"duplicate_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_s-kHcqNBUNO6nOGjnPkiu","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 supplied duplicate-observation records (duplicate_rows, total_rows) to produce numeric row ordering and IQR-based outlier flag reports, up to 200 rows, with two independent analytical reports per call.","exampleAgentPrompt":"Can you analyze these dataset duplicate-row records and give me both a numeric row ordering and IQR outlier flags for the duplicate_rows field? I have 4 records: row-1 on 2026-10-01 in group-a with 10 duplicate_rows out of 1 total, row-2 on 2026-10-02 in group-b with 20 duplicate_rows out of 2 total, row-3 on 2026-10-03 in group-a with 15 duplicate_rows out of 3 total, and row-4 on 2026-10-04 in group-b with 30 duplicate_rows out of 4 total.","exampleUseCases":[{"title":"Data quality audit for ETL pipeline","prompt":"I have daily dataset snapshots from our ETL pipeline — can you analyze these duplicate_rows counts across groups and tell me which records are IQR outliers and how they rank numerically? Here are the rows: row-1 on 2026-11-01 in group-etl with 50 duplicate_rows out of 1000 total, row-2 on 2026-11-02 in group-etl with 300 duplicate_rows out of 1000 total, row-3 on 2026-11-03 in group-etl with 55 duplicate_rows out of 1000 total. Use the duplicate_rows field."},{"title":"Monitoring duplication spikes across dataset groups","prompt":"We track duplicate row counts across several dataset groups daily. Can you rank these 5 records by their total_rows values and flag any IQR outliers? Records: row-A on 2026-12-01 in group-sales with 80 duplicate_rows out of 500 total, row-B on 2026-12-02 in group-sales with 82 duplicate_rows out of 510 total, row-C on 2026-12-03 in group-ops with 900 duplicate_rows out of 520 total, row-D on 2026-12-04 in group-ops with 78 duplicate_rows out of 495 total, row-E on 2026-12-05 in group-sales with 79 duplicate_rows out of 505 total. Analyze the total_rows field."},{"title":"Pre-merge data validation for analyst team","prompt":"Before we merge these dataset exports, I need to check for outlier duplication rates — can you run numeric row ordering and IQR outlier flags on the duplicate_rows field for these records? row-X on 2027-01-10 in group-finance with 12 duplicate_rows out of 200 total, row-Y on 2027-01-11 in group-finance with 14 duplicate_rows out of 210 total, row-Z on 2027-01-12 in group-finance with 150 duplicate_rows out of 205 total."}],"resultDescription":"Returns two independent analytical reports per call: (1) numeric row ordering of the submitted records ranked by the selected field (duplicate_rows or total_rows), and (2) IQR-based outlier flags identifying which rows fall outside the interquartile range. No external data is fetched; all analysis is performed locally on the supplied data.","failureModes":["Fewer than 1 or more than 200 rows submitted — request rejected","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Null values in both numeric fields may reduce IQR calculation accuracy","row_id or dataset_group exceeding 80 characters — validation error","Field enum value other than 'duplicate_rows' or 'total_rows' — rejection"],"whenToPreferThis":"Choose this endpoint when you have structured duplicate-observation records with row-level duplicate_rows and total_rows counts and need both ranked ordering and IQR-based outlier detection in a single call. It is ideal for lightweight, local data quality audits of up to 200 rows where no external data access, prediction, or live lookup is required. At $0.01 USDC for two reports, it is cost-effective for batch data quality checks on ETL outputs, dataset merges, or periodic data audits.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:39:44.803Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-analytics-numeric-row-ordering-iqr-outlier-flags-11df0fba"}