{"uid":"cap_bckrqbnqKQ1UHB1JcBBvL","slug":"travel-administration-category-frequencies-iqr-outlier-flags-bf143d9d","name":"Travel Administration — Category Frequencies + IQR Outlier Flags","description":"Travel administration — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied travel administration records (trip_count, recorded_cost). 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-operations-14-107?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","trip_count","recorded_cost"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"trip_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"recorded_cost":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","trip_count":10,"recorded_cost":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","trip_count":20,"recorded_cost":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","trip_count":15,"recorded_cost":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","trip_count":30,"recorded_cost":4}],"maxItems":200,"minItems":1},"field":{"enum":["trip_count","recorded_cost"],"type":"string","default":"trip_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_3ihYiySBFExsFOX3zYpGm","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":"Computes category frequencies and IQR-based outlier flags for travel administration records (trip_count, recorded_cost) across up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you analyze my travel administration records for category frequencies and flag any IQR outliers in trip_count? Here are the rows: group-a on 2026-10-01 had 10 trips costing $1, group-b on 2026-10-02 had 20 trips costing $2, group-a on 2026-10-03 had 15 trips costing $3, group-b on 2026-10-04 had 200 trips costing $4 — that last one looks suspicious.","exampleUseCases":[{"title":"Expense audit for travel team","prompt":"I have 50 rows of travel records from our ops team — can you run a frequency breakdown by team_group and flag any recorded_cost values that are IQR outliers? I want to catch any unusual expense entries before we close the books."},{"title":"Trip count anomaly detection","prompt":"Here's our monthly travel data across 4 team groups with dates and trip counts — please compute category frequencies and use IQR outlier detection on trip_count so I can see which entries look statistically abnormal."},{"title":"Cross-team travel pattern summary","prompt":"We have travel administration records for groups alpha, beta, and gamma over the past quarter. Can you give me a frequency count of entries per team and flag any trip_count outliers beyond 1.5 times the IQR?"}],"resultDescription":"Returns two independent reports: (1) category frequency counts showing how often each team_group appears in the dataset, and (2) IQR outlier flags for the selected numeric field (trip_count or recorded_cost), indicating which rows fall beyond 1.5× the interquartile range. No live lookups or external data are used — analysis is performed entirely on the supplied rows.","failureModes":["Fewer than 1 row supplied — minimum row count not met","More than 200 rows supplied — exceeds maximum row limit","Missing required fields (row_id, team_group, date, trip_count, recorded_cost) in any row","Invalid date format (must be YYYY-MM-DD)","Invalid field enum value (must be 'trip_count' or 'recorded_cost')","All numeric values are null — IQR cannot be computed","row_id or team_group exceeds 80-character limit"],"whenToPreferThis":"Choose this endpoint when you need both a category frequency summary and IQR-based outlier detection on travel administration records in a single $0.01 call covering up to 200 rows. Prefer it over generic statistics APIs when your data has the specific travel schema (trip_count, recorded_cost, team_group) and you want two bundled reports without external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:54.057Z","isFirstParty":false,"canonicalSlug":"travel-administration-category-frequencies-iqr-outlier-flags-bf143d9d"}