{"uid":"cap_-RM_FjPd1GZPh8crvQbJB","slug":"duplicate-observations-exact-row-deduplication-iqr-outlier-flags-151bb080","name":"Duplicate Observations — Exact Row Deduplication + IQR Outlier Flags","description":"Duplicate observations — Exact row deduplication + IQR outlier flags: Exact row deduplication + 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-04-049?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_E2m_TgjetvIHxQn-znIiP","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":"Performs exact row deduplication and IQR-based outlier flagging on up to 200 duplicate observation records containing duplicate_rows and total_rows metrics.","exampleAgentPrompt":"Can you run exact row deduplication and IQR outlier flagging on my duplicate observation records? I have 4 rows across two groups — group-a and group-b — from 2026-10-01 to 2026-10-04, with duplicate_rows values of 10, 20, 15, and 30, and total_rows of 1 through 4. Analyze the duplicate_rows field.","exampleUseCases":[{"title":"Data pipeline quality audit","prompt":"I have daily data quality logs from two dataset groups — 'warehouse' and 'staging' — for the past week, with duplicate_rows and total_rows counts per day. Can you deduplicate the exact rows and flag any IQR outliers in the duplicate_rows field so I can see which days had abnormal duplication?"},{"title":"ETL monitoring anomaly detection","prompt":"My ETL process tracks duplicate observations every day across three groups: 'orders', 'customers', and 'products'. Here are 12 rows of data with row IDs, dates, duplicate_rows, and total_rows — can you run IQR outlier detection on total_rows and also do exact row deduplication to clean up the report?"},{"title":"Data quality dashboard pre-processing","prompt":"Before building our data quality dashboard, I need to clean up these 30 observation records from groups 'raw' and 'processed' — dates ranging from 2026-09-01 to 2026-09-30 — by removing exact duplicate rows and flagging any duplicate_rows values that are statistical outliers using IQR. Can you do both reports?"}],"resultDescription":"Returns two independent analytical reports: (1) an exact row deduplication report identifying and removing identical records from the input, and (2) an IQR outlier flagging report that identifies which records have statistically anomalous values (beyond the interquartile range fences) in the selected field (duplicate_rows or total_rows). Results are computed locally without external lookups.","failureModes":["More than 200 rows submitted — input exceeds maxItems limit","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — validation error","Date field not matching YYYY-MM-DD pattern — schema validation failure","Invalid field enum value (must be 'duplicate_rows' or 'total_rows') — rejected request","Empty rows array — minItems constraint violation","Non-numeric values for duplicate_rows or total_rows — type validation error"],"whenToPreferThis":"Choose this endpoint when you need both exact row deduplication AND IQR-based statistical outlier detection on duplicate observation metrics in a single call. It is best suited for data quality pipelines, ETL monitoring, or pre-processing workflows where you have structured records with duplicate_rows and total_rows counts grouped by dataset and date. Prefer this over single-report endpoints when you want two complementary analyses (deduplication + outlier flagging) at once for up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:18.537Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-exact-row-deduplication-iqr-outlier-flags-151bb080"}