{"uid":"cap_FBSYvoW5O-lPiPBWvqtjZ","slug":"travel-administration-iqr-outlier-flags-date-by-category-pivot-5cbaa5e0","name":"Travel Administration IQR Outlier Flags + Date by Category Pivot","description":"Travel administration — IQR outlier flags + Date by category pivot: IQR outlier flags + Date by category pivot 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-14-178?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_W1Ct5YedpTQ9UvAF4jlm5","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 supplied travel administration data: IQR-based outlier detection and a date-by-category pivot, for up to 200 rows of trip_count or recorded_cost data.","exampleAgentPrompt":"Can you analyze these travel records for my team groups — run IQR outlier detection on recorded_cost and also give me a date-by-category pivot? Here are up to 200 rows with row_id, team_group, date, trip_count, and recorded_cost.","exampleUseCases":[{"title":"Expense anomaly detection for finance review","prompt":"I have 150 rows of corporate travel data with trip counts and recorded costs per team group — can you flag any outliers in recorded_cost using IQR and also pivot those records by date and team category?"},{"title":"Monthly travel audit across departments","prompt":"Run an outlier analysis and a date-by-team-group pivot on these travel administration records for trip_count — I need to see which dates or groups look statistically unusual before I submit the monthly report."},{"title":"Team travel cost comparison and anomaly flagging","prompt":"Here are travel records for group-a and group-b over the past quarter — flag any IQR outliers in the recorded_cost field and give me a pivot table breaking it down by date and team category."}],"resultDescription":"Returns two analytical reports: (1) IQR outlier flags identifying rows whose trip_count or recorded_cost values fall outside the interquartile range, and (2) a pivot table aggregating values by date and team_group category — both computed locally from the supplied data, no external lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, team_group, date, trip_count, recorded_cost) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Numeric values outside allowed range (±1,000,000,000,000) — rejection","Empty rows array — no data to process"],"whenToPreferThis":"Choose this endpoint when you need fast, self-contained statistical analysis of travel administration records — specifically IQR-based outlier detection plus date-by-category pivoting — on batches of up to 200 rows, without needing external data lookups, predictions, or live enrichment. Best suited for finance, ops, or admin teams doing periodic audits of team travel costs and trip counts.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:22.058Z","isFirstParty":false,"canonicalSlug":"travel-administration-iqr-outlier-flags-date-by-category-pivot-5cbaa5e0"}