{"uid":"cap_uTkAOVU5SRnZBIgfxw7mA","slug":"duplicate-observations-numeric-row-ordering-and-interval-filter-5fd1b0ce","name":"Duplicate Observations Numeric Row Ordering and Interval Filter Analytics","description":"Duplicate observations — Numeric row ordering + Numeric interval filter: Numeric row ordering + Numeric interval filter 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-04-113?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_wOkDAJRFDZr8HExkaFNey","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 by applying numeric row ordering and interval filtering on duplicate_rows or total_rows fields, returning up to 2 analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 4 dataset observations with duplicate counts — row-1 from group-a on 2026-10-01 has 10 duplicate_rows out of 1 total, row-2 from group-b on 2026-10-02 has 20 duplicate_rows out of 2 total, and so on — can you order them numerically and filter to only show rows where duplicate_rows is between 0 and 25, giving me 2 reports?","exampleUseCases":[{"title":"Data quality audit by duplicate rate","prompt":"I have a list of 50 dataset observations across groups A and B with their duplicate_rows and total_rows counts for October. Can you run numeric row ordering and filter to only show rows where duplicate_rows is between 5 and 50, and give me the 2 analytical reports?"},{"title":"Threshold-based duplicate spike detection","prompt":"Here are 120 dataset records with duplicate and total row counts — I want them ordered numerically and filtered so I only see entries where total_rows falls between 100 and 500. Run the interval filter on the total_rows field and return both reports."},{"title":"Group-level duplicate observation ranking","prompt":"I've got observations from three dataset groups with duplicate_rows values ranging from 0 to 200. Please order them numerically and filter for rows where duplicate_rows is between 10 and 80, covering all 200 rows I'm supplying."}],"resultDescription":"Returns up to 2 analytical reports based on the supplied rows: one applying numeric row ordering and one applying a numeric interval filter on the chosen field (duplicate_rows or total_rows). Each report covers up to 200 input rows and is computed entirely from the supplied data using local analytical engines — no external lookups or predictions are made.","failureModes":["Exceeding 200 rows in the input array returns a validation error","Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) causes schema validation failure","Invalid date format (not YYYY-MM-DD) triggers a pattern mismatch error","Minimum value greater than maximum value may produce empty interval-filter results","Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected","Empty rows array (minItems: 1 not met) returns a validation error"],"whenToPreferThis":"Choose this endpoint when you have pre-collected duplicate observation records (with duplicate_rows and total_rows counts per dataset group and date) and need both numeric ordering and interval-based filtering in a single low-cost call. It is ideal for data quality workflows where you want to rank rows and isolate those within a specific numeric range without any external data lookups or ML predictions. At $0.01 per call for 2 reports and up to 200 rows, it is cost-effective for batch data-quality auditing tasks.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T06:50:10.832Z","isFirstParty":false,"canonicalSlug":"duplicate-observations-numeric-row-ordering-and-interval-filter-5fd1b0ce"}