{"uid":"cap_BcVK08MCcqGsKXdhPPFbu","slug":"customer-segment-observations-exact-row-deduplication-explicit-a2f6d54e","name":"Customer Segment Observations — Exact Row Deduplication + Explicit Missing-Value Fill","description":"Customer segment observations — Exact row deduplication + Explicit missing-value fill: Exact row deduplication + Explicit missing-value fill for supplied customer segment observations records (account_count, revenue_amount). 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-company-16-054?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","account_count","revenue_amount"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"account_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"revenue_amount":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","account_count":10,"company_group":"group-a","revenue_amount":1},{"date":"2026-10-02","row_id":"row-2","account_count":20,"company_group":"group-b","revenue_amount":2},{"date":"2026-10-03","row_id":"row-3","account_count":15,"company_group":"group-a","revenue_amount":3},{"date":"2026-10-04","row_id":"row-4","account_count":30,"company_group":"group-b","revenue_amount":4}],"maxItems":200,"minItems":1},"field":{"enum":["account_count","revenue_amount"],"type":"string","default":"account_count"},"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_AiEVMijZtIIch5mVGYHLB","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":"Deduplicates exact duplicate rows and fills missing values (account_count or revenue_amount) in customer segment observation records using zero, mean, or median imputation.","exampleAgentPrompt":"Can you clean up my customer segment observations dataset — it has up to 150 rows with company_group, date, account_count, and revenue_amount fields — by removing exact duplicate rows and filling any missing revenue_amount values using median imputation?","exampleUseCases":[{"title":"Monthly segment revenue data cleanup","prompt":"I have 120 rows of customer segment observations by company group and date, and some revenue_amount values are null — can you deduplicate the rows and fill in those missing revenue amounts using the median?"},{"title":"Account count gap filling for analytics pipeline","prompt":"Before I run my segment analytics, I need to clean this dataset of up to 80 customer segment records: remove any exact duplicate rows and fill missing account_count values with zero."},{"title":"Pre-report data quality pass on segment observations","prompt":"I've got a batch of 200 customer segment observation rows across multiple company groups — please deduplicate them and use mean imputation to fill any missing account_count values so the data is ready for reporting."}],"resultDescription":"Returns two analytical reports for the submitted customer segment observation records: one covering exact row deduplication (identifying and removing fully duplicate rows) and one covering explicit missing-value fill for the specified field (account_count or revenue_amount) using the chosen method (zero, mean, or median). Supports up to 200 input rows.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, company_group, date) on any row — validation error","Invalid date format (must be YYYY-MM-DD) — schema rejection","Numeric values outside allowed range (±1,000,000,000,000) — rejected","Empty rows array — minItems:1 violation","Invalid method enum value (not zero/mean/median) — schema error","Invalid field enum value (not account_count/revenue_amount) — schema error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 customer segment observation records (with account_count and/or revenue_amount fields) that need both exact duplicate row removal and structured missing-value imputation in a single call. It is purpose-built for this specific schema (company_group, date, account_count, revenue_amount) and delivers two reports for a fixed $0.01 USDC. Prefer it over generic data-cleaning pipelines when your data fits this customer segment structure and you need lightweight, local analytical processing without any external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:48.633Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-exact-row-deduplication-explicit-a2f6d54e"}