{"uid":"cap_U37nnnN9I6kYhvPG5ScSa","slug":"duplicate-observations-iqr-outlier-flags-and-date-by-category-pivot-b49e42a5","name":"Duplicate Observations IQR Outlier Flags and Date-by-Category Pivot","description":"Duplicate observations — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot 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-04-178?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_tqzKknsCwBoXBBRjp0aMH","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 to produce two offline reports: IQR-based outlier flags and a date-by-category pivot table, for up to 200 rows.","exampleAgentPrompt":"I have up to 200 rows of duplicate-observation records with columns row_id, dataset_group, date, duplicate_rows, and total_rows — can you run the IQR outlier flagging and date-by-category pivot on the duplicate_rows field and show me which records are outliers and how the values break down across groups by date?","exampleUseCases":[{"title":"Data pipeline deduplication audit","prompt":"I'm auditing our ETL pipeline and have 150 rows of daily duplicate counts per dataset group from the past quarter — can you flag any IQR outliers in duplicate_rows and pivot the counts by date and group so I can spot which days and groups are problematic?"},{"title":"Data quality regression after schema change","prompt":"After our schema migration last month, I want to check if duplicate_rows spiked abnormally in any dataset group — here are 80 records with row_id, dataset_group, date, duplicate_rows, and total_rows. Please flag outliers using IQR and give me a date-by-category breakdown."},{"title":"Comparing duplication across teams' datasets","prompt":"I have 60 records tracking duplicate_rows and total_rows across five team dataset groups over the last two weeks — run the IQR outlier flags and a date-by-category pivot on duplicate_rows so I can see which teams have abnormal duplication patterns."}],"resultDescription":"Two local analytical reports: (1) an IQR outlier flag report marking which input records have duplicate_rows or total_rows values outside the interquartile range, and (2) a date-by-category pivot table cross-tabulating the selected numeric field by date and dataset_group — all computed offline without external lookups.","failureModes":["Fewer than 1 row submitted — returns a validation error","More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — schema validation failure","Malformed date format (not YYYY-MM-DD) — pattern validation rejection","Null numeric values that reduce effective sample size for IQR computation — may produce degenerate outlier flags","Invalid field enum value (not duplicate_rows or total_rows) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have batch duplicate-observation records (up to 200 rows) and need both IQR outlier detection and a date-by-category pivot in a single low-cost call. Prefer it over generic statistics APIs when your data is structured around dataset_group, date, duplicate_rows, and total_rows and you want two coordinated offline analytical reports without live lookups or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-18T00:58:21.965Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-iqr-outlier-flags-and-date-by-category-pivot-b49e42a5"}