{"uid":"cap_6-MnzEk77U7ibD07uoPQy","slug":"customer-segment-observations-iqr-outlier-flags-date-by-category-pivot-fa2d0cc8","name":"Customer Segment Observations – IQR Outlier Flags + Date by Category Pivot","description":"Customer segment observations — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot 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-16-178?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_a7zD85fuuELOuoswLM7BP","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":"Runs two local analytical reports on customer segment observation data: IQR-based outlier detection and a date-by-category pivot table, for up to 200 rows of account_count or revenue_amount data.","exampleAgentPrompt":"I have 150 rows of customer segment observations with account_count and revenue_amount by company_group and date — can you run IQR outlier flagging and a date-by-category pivot on the revenue_amount field?","exampleUseCases":[{"title":"Revenue outlier detection for segments","prompt":"I've got monthly revenue observations for about 80 customer segments across multiple company groups — can you flag which rows are IQR outliers and pivot the revenue_amount data by date and category so I can spot unusual spikes?"},{"title":"Account count anomaly scan","prompt":"Here are 120 rows of customer segment data with account counts per company group by date. Run the IQR outlier flags and date-by-category pivot on the account_count field so I can see which segments have abnormal counts."},{"title":"Pivot and outlier report for BI dashboard","prompt":"I need a quick analytical report on these 60 customer segment observation records — run both the IQR outlier detection and the date-by-category pivot on revenue_amount and give me the results so I can load them into our dashboard."}],"resultDescription":"Returns two independent analytical reports: (1) IQR outlier flags indicating which rows in the supplied data fall outside the interquartile range for the selected field (account_count or revenue_amount), and (2) a date-by-category pivot table summarizing values across company_group and date dimensions. All computation is local with no external data lookups.","failureModes":["Fewer than 1 row supplied — minItems validation failure","More than 200 rows supplied — maxItems exceeded","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Missing required fields (row_id, company_group, date, account_count, revenue_amount) — schema validation error","Invalid field enum value (must be account_count or revenue_amount)","Numeric values outside allowed range (±1,000,000,000,000)","Payment not included or insufficient USDC — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local statistical analysis on customer segment observations without any external lookup or prediction — specifically when you want both IQR outlier detection and a date-by-category pivot in a single low-cost call ($0.01 USDC for both reports). Ideal for batch analytical preprocessing of up to 200 rows of account_count or revenue_amount data grouped by company_group and date.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T12:44:54.821Z","isFirstParty":false,"canonicalSlug":"customer-segment-observations-iqr-outlier-flags-date-by-category-pivot-fa2d0cc8"}