{"uid":"cap_cPKUxcn7duQaIoFUCdctt","slug":"travel-administration-iqr-outlier-flags-explicit-missing-value-fill-4fcb9718","name":"Travel Administration IQR Outlier Flags + Explicit Missing-Value Fill","description":"Travel administration — IQR outlier flags + Explicit missing-value fill: IQR outlier flags + Explicit missing-value fill 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-14-180?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_Df9dRFLXPGmZXan-XqZQv","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":"Detects IQR-based outliers and fills missing values in travel administration records (trip_count, recorded_cost) for up to 200 rows, producing two independent analytical reports.","exampleAgentPrompt":"Can you flag any IQR outliers and fill missing values using median imputation in my travel administration records for the Finance team — I have up to 50 rows with trip_count and recorded_cost fields that need cleaning?","exampleUseCases":[{"title":"Corporate travel expense audit","prompt":"I have 120 rows of corporate travel data with trip_count and recorded_cost per team group — can you flag any statistical outliers using IQR and fill in any missing recorded_cost values using the mean?"},{"title":"Monthly travel report data cleanup","prompt":"Before I generate our monthly travel report, can you run IQR outlier detection on our 80-row dataset and fill any null trip_count entries with the median so the numbers are clean?"},{"title":"Team travel anomaly detection","prompt":"I need to identify suspicious trip counts and costs across our regional teams — can you flag IQR-based outliers and use zero-fill for any missing recorded_cost values across these 60 travel records?"}],"resultDescription":"Two independent analytical reports: (1) an IQR outlier flags report marking which rows contain statistically extreme values for the specified field, and (2) an explicit missing-value fill report showing where nulls were replaced using the chosen method (zero, mean, or median). Results are computed locally with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Invalid date format (not YYYY-MM-DD) causes rejection","Missing required fields (row_id, team_group, date, trip_count, recorded_cost) cause schema validation failure","Numeric values outside ±1,000,000,000,000 are rejected","Invalid method enum value (not zero/mean/median) returns error","Invalid field enum value (not trip_count/recorded_cost) returns error"],"whenToPreferThis":"Choose this endpoint when you have travel administration tabular data (up to 200 rows) with trip_count and/or recorded_cost fields that need both statistical outlier detection (IQR-based) and missing value imputation in a single low-cost call. Ideal for pre-processing travel expense datasets before reporting or further analysis, when no live data lookup, ML prediction, or external enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T12:42:30.636Z","isFirstParty":false,"canonicalSlug":"travel-administration-iqr-outlier-flags-explicit-missing-value-fill-4fcb9718"}