{"uid":"cap_MnU3cOspB02UwGVQRB5V2","slug":"travel-administration-numeric-interval-filter-and-iqr-outlier-flags-12909045","name":"Travel Administration Numeric Interval Filter and IQR Outlier Flags","description":"Travel administration — Numeric interval filter + IQR outlier flags: Numeric interval filter + 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-14-130?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"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_lPi9YIloLqUUQ6Qm66ch8","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":"Filters travel administration records by a numeric interval and flags IQR-based outliers for trip_count or recorded_cost fields across up to 200 rows in two reports.","exampleAgentPrompt":"Can you run an interval filter and IQR outlier check on our travel records for the recorded_cost field, keeping only rows between 50 and 5000, and flag any statistical outliers? Here are up to 200 rows with row_id, team_group, date, trip_count, and recorded_cost.","exampleUseCases":[{"title":"Corporate travel cost anomaly detection","prompt":"I have 150 rows of corporate travel data with trip counts and costs per team. Can you filter recorded_cost between 200 and 8000 and flag any IQR outliers so I can spot which team groups are spending abnormally?"},{"title":"Trip count range filtering for quarterly review","prompt":"Run a numeric interval filter on our travel administration records for trip_count between 5 and 50, and also flag any outliers using IQR — I need two reports covering all 180 rows we logged this quarter."},{"title":"Audit travel data for data quality issues","prompt":"We suspect some of our recorded travel costs are erroneous. Can you filter our 90 travel rows where recorded_cost is between 0 and 10000 and use IQR outlier flags to highlight which entries look statistically suspicious?"}],"resultDescription":"Returns two analytical reports: one filtering input travel rows where the selected field (trip_count or recorded_cost) falls within the specified minimum-maximum interval, and a second report flagging rows as IQR outliers based on interquartile range analysis of the same field. Each row retains its row_id, team_group, date, and numeric fields.","failureModes":["Fewer than 1 row supplied returns a validation error","More than 200 rows supplied exceeds the limit and is rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Null values in the selected numeric field may reduce outlier detection accuracy","minimum greater than maximum may return zero matching rows without error","Missing required row fields (row_id, date) causes request rejection"],"whenToPreferThis":"Choose this endpoint when you have tabular travel administration data (up to 200 rows) and need both a numeric range filter and IQR-based outlier detection on trip_count or recorded_cost in a single low-cost call. It is ideal for lightweight, local statistical analysis without needing a live data connection, prediction, or external lookup. Prefer alternatives if you need more than 200 rows, real-time data enrichment, or multi-field correlation analysis.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-27T13:06:44.781Z","isFirstParty":false,"canonicalSlug":"travel-administration-numeric-interval-filter-and-iqr-outlier-flags-12909045"}