{"uid":"cap_QQ3_w2EJ4Z-KxQs4yf9Fl","slug":"customer-segment-observations-exact-row-deduplication-iqr-outlier-flags-644798d0","name":"Customer Segment Observations — Exact Row Deduplication + IQR Outlier Flags","description":"Customer segment observations — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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-16-049?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"}}},"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_0fp4aL1SM-6s1uDq7XAll","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 rows and flags IQR-based outliers in customer segment observation records containing account_count and revenue_amount fields, producing two analytical reports for up to 200 rows.","exampleAgentPrompt":"Can you deduplicate and flag IQR outliers on my customer segment observations? I have rows with company_group, date, account_count, and revenue_amount — analyze the revenue_amount field, up to 200 rows, and give me both reports.","exampleUseCases":[{"title":"Revenue outlier detection by segment","prompt":"I have monthly customer segment data with company groups, dates, and revenue amounts — can you run IQR outlier flagging on the revenue_amount field and also deduplicate any exact duplicate rows? Here are my records: group-a on 2026-01-01 with 500 accounts and $12000 revenue, group-b on 2026-01-02 with 450 accounts and $980000 revenue, etc."},{"title":"Account count anomaly audit","prompt":"Can you check my customer segment observations for exact duplicate rows and flag any anomalous account_count values using IQR? I want to clean up this dataset before I run our quarterly analysis — I'll send you up to 150 rows with row_id, company_group, date, and account_count."},{"title":"Pre-pipeline data quality check","prompt":"Before I load this segment data into our BI tool, can you deduplicate it and flag any IQR outliers in the revenue_amount column? I've got about 80 rows across several company groups spanning Q3 2026."}],"resultDescription":"Two analytical reports: (1) an exact row deduplication report identifying which rows are exact duplicates, and (2) an IQR outlier flagging report marking rows whose selected numeric field (account_count or revenue_amount) falls outside the interquartile range bounds. Both reports are generated locally without external lookups.","failureModes":["Exceeding 200-row limit causes rejection","Missing required fields (row_id, company_group, date, account_count, revenue_amount) causes validation error","Invalid date format (not YYYY-MM-DD) causes parsing failure","Providing fewer than 1 row causes error","Field value outside allowed numeric range causes rejection","IQR computation may be unreliable with very small datasets (fewer than 4 rows)"],"whenToPreferThis":"Choose this endpoint when you have customer segment observation records with account_count and/or revenue_amount fields and need both duplicate removal and statistical outlier detection in a single low-cost call. Ideal for pre-pipeline data quality checks on datasets up to 200 rows. Prefer this over generic data quality tools when your data is specifically structured around company groups, dates, and segment-level numeric metrics.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T12:48:52.071Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-exact-row-deduplication-iqr-outlier-flags-644798d0"}