{"uid":"cap_oIJo7TF5lC4ylvggAdJWh","slug":"business-event-participation-numeric-row-ordering-iqr-outlier-flags-7f35b916","name":"Business Event Participation — Numeric Row Ordering + IQR Outlier Flags","description":"Business event participation — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags for supplied business event participation records (attendee_count, company_count). 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-19-119?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","attendee_count","company_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"company_group":{"type":"string","default":"","maxLength":80},"attendee_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_count":1,"company_group":"group-a","attendee_count":10},{"date":"2026-10-02","row_id":"row-2","company_count":2,"company_group":"group-b","attendee_count":20},{"date":"2026-10-03","row_id":"row-3","company_count":3,"company_group":"group-a","attendee_count":15},{"date":"2026-10-04","row_id":"row-4","company_count":4,"company_group":"group-b","attendee_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["attendee_count","company_count"],"type":"string","default":"attendee_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_-3zHByg9jO_ikxKokTywF","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":"Ranks rows by attendee_count or company_count and flags statistical outliers using the IQR method across up to 200 business event participation records, producing two independent analytical reports.","exampleAgentPrompt":"I have 4 business event records with attendee and company counts — can you rank them numerically by attendee_count and flag any IQR outliers? The rows are: row-1 (group-a, 2026-10-01, 10 attendees, 1 company), row-2 (group-b, 2026-10-02, 20 attendees, 2 companies), row-3 (group-a, 2026-10-03, 15 attendees, 3 companies), row-4 (group-b, 2026-10-04, 30 attendees, 4 companies).","exampleUseCases":[{"title":"Flagging outlier events in a conference series","prompt":"I have 8 quarterly conference records with attendee and company counts — rank them by attendee_count and tell me which ones are statistical outliers based on IQR. Here are the rows: row-1 (corp-a, 2025-01-15, 120 attendees, 10 companies), row-2 (corp-b, 2025-04-20, 450 attendees, 35 companies), row-3 (corp-a, 2025-07-10, 130 attendees, 11 companies), row-4 (corp-b, 2025-10-05, 140 attendees, 12 companies), row-5 (corp-a, 2026-01-18, 125 attendees, 10 companies), row-6 (corp-b, 2026-04-22, 115 attendees, 9 companies), row-7 (corp-a, 2026-07-14, 960 attendees, 80 companies), row-8 (corp-b, 2026-10-01, 130 attendees, 11 companies)."},{"title":"Ranking trade show participation by company count","prompt":"Can you rank these 5 trade show records by company_count and flag any IQR outliers? row-1 (retail-group, 2026-03-01, 200 attendees, 18 companies), row-2 (tech-group, 2026-03-02, 310 attendees, 27 companies), row-3 (retail-group, 2026-03-03, 190 attendees, 16 companies), row-4 (tech-group, 2026-03-04, 205 attendees, 95 companies), row-5 (retail-group, 2026-03-05, 215 attendees, 19 companies)."},{"title":"Auditing event attendance anomalies for a report","prompt":"I need to audit our 6 annual networking events for attendance anomalies — rank them by attendee_count and tell me which ones fall outside the IQR bounds. Events: row-1 (east-region, 2024-02-10, 80 attendees, 8 companies), row-2 (west-region, 2024-05-15, 85 attendees, 7 companies), row-3 (east-region, 2024-08-20, 400 attendees, 6 companies), row-4 (west-region, 2024-11-10, 90 attendees, 9 companies), row-5 (east-region, 2025-02-12, 78 attendees, 8 companies), row-6 (west-region, 2025-05-18, 82 attendees, 7 companies)."}],"resultDescription":"Returns two independent analytical reports for the submitted rows: (1) a numeric row ordering report ranking all rows by the selected field (attendee_count or company_count), and (2) an IQR outlier flags report identifying which rows fall outside the interquartile range bounds for that field. No external lookups or predictions are made — all computation is performed locally on the supplied data.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, company_group, date, attendee_count, company_count) cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern fail schema validation","Too few rows (fewer than 1) to compute meaningful IQR — IQR flags may be trivial or undefined","Invalid field enum value (not attendee_count or company_count) causes request rejection","Null values in the target field may affect ordering and outlier computation accuracy"],"whenToPreferThis":"Choose this endpoint when you have structured business event participation records (up to 200 rows) and need both a ranked ordering and IQR-based outlier detection in a single call for either attendee_count or company_count. It is ideal for lightweight, offline statistical analysis without requiring a full analytics platform, and is cost-effective at $0.01 USDC for two reports simultaneously. Prefer it over generic statistical tools when your data already fits the schema of event rows with company_group, date, and participation counts.","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":"business-event-participation-numeric-row-ordering-iqr-outlier-flags-7f35b916"}