{"uid":"cap_PmCPP-XhsRMEzJpOUHSnc","slug":"duplicate-observations-analyzer-numeric-row-ordering-explicit-missing-6fd97e91","name":"Duplicate Observations Analyzer — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Duplicate observations — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill 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-04-124?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_a3qONC_K9-Aa5B_8cuZxj","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 records of duplicate-observation data, applying numeric row ordering and explicit missing-value fill (zero, mean, or median) to either the duplicate_rows or total_rows field, returning 2 analytical reports.","exampleAgentPrompt":"I have 4 rows of duplicate observation data for groups A and B dated 2026-10-01 through 2026-10-04 — can you analyze the duplicate_rows field using median fill to handle any missing values and give me the numeric row ordering plus fill reports?","exampleUseCases":[{"title":"Data quality audit for ETL pipeline","prompt":"I've got daily duplicate row counts for 3 dataset groups over the past month — some values are missing. Can you run the numeric row ordering and fill in the missing duplicate_rows values using median, then give me both reports?"},{"title":"Total rows baseline with zero-fill","prompt":"Here are 50 records with total_rows and duplicate_rows counts per dataset group. Analyze total_rows with zero fill for any nulls and apply numeric row ordering so I can see the ordered baseline report."},{"title":"Mean-fill imputation for duplicate counts","prompt":"I have observations across group-a and group-b with some null duplicate_rows entries. Can you apply mean fill to those missing values and order the rows numerically so I get a clean analytics report on the duplicate counts?"}],"resultDescription":"Returns 2 independent analytical reports: one applying numeric row ordering to the supplied rows, and one applying explicit missing-value fill (zero, mean, or median) to the selected field (duplicate_rows or total_rows). Reports are computed locally from supplied data with no external lookups.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation errors","Invalid date format (not YYYY-MM-DD) rejected by pattern validation","Invalid method enum value (not zero, mean, or median) causes error","Invalid field enum value (not duplicate_rows or total_rows) causes error","Numeric values outside ±1,000,000,000,000 range rejected"],"whenToPreferThis":"Choose this endpoint when you have tabular duplicate-observation records (up to 200 rows) and need both numeric ordering of rows and explicit missing-value imputation applied to duplicate_rows or total_rows fields in a single call. Ideal for data quality workflows where you want offline, deterministic analytics without any external data lookups or live predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:34.730Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-analyzer-numeric-row-ordering-explicit-missing-6fd97e91"}