{"uid":"cap_uPiXbsWcTh3h1wZaxdn3I","slug":"transport-ridership-category-frequencies-iqr-outlier-flags-a3cce835","name":"Transport Ridership Category Frequencies & IQR Outlier Flags","description":"Transport ridership — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags for supplied transport ridership records (passenger_count, service_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-economics-05-107?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","region","date","passenger_count","service_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"service_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"passenger_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","service_count":1,"passenger_count":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","service_count":2,"passenger_count":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","service_count":3,"passenger_count":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","service_count":4,"passenger_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["passenger_count","service_count"],"type":"string","default":"passenger_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_bELcQ0Rdhfg2Aty5ckavk","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-level frequency counts and flags IQR-based outliers for transport ridership records (passenger_count or service_count) across up to 200 rows.","exampleAgentPrompt":"Analyze my transit dataset for category frequencies and IQR outlier flags on passenger_count — I have 4 rows: row-1 (2026-10-01, group-a, passenger_count=10, service_count=1), row-2 (2026-10-02, group-b, 20, 2), row-3 (2026-10-03, group-a, 15, 3), row-4 (2026-10-04, group-b, 30, 4). Give me both the frequency report and the outlier flags.","exampleUseCases":[{"title":"Detecting anomalous passenger counts by region","prompt":"I have 50 daily ridership records across regions North, South, and East — can you compute the category frequencies by region and flag any passenger_count outliers using IQR? Here are the rows with row_id, date, region, passenger_count, and service_count."},{"title":"Service count distribution audit for transit planner","prompt":"Run a frequency and IQR outlier analysis on my service_count field across these 120 transport ridership records grouped by region — I want to know which categories are most common and which rows have statistically unusual service counts."},{"title":"Quality check on regional ridership data before reporting","prompt":"Before I submit this month's ridership report, can you check my 80 records for category frequency patterns and flag any IQR outliers in both passenger_count and service_count? I'll send you the rows with region, date, and both count fields."}],"resultDescription":"Returns two independent analytical reports: (1) category frequency counts showing how many records fall into each region/category group, and (2) IQR-based outlier flags identifying which rows have statistically unusual values for the selected field (passenger_count or service_count). Both reports are computed locally without external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Missing required fields (row_id, region, date, passenger_count, service_count) cause validation errors","Invalid date format (must match YYYY-MM-DD pattern) causes schema rejection","Numeric values outside the allowed range (-1e12 to 1e12) rejected","Empty rows array (minItems: 1 violated) causes error","All-null values in selected field may produce empty or degenerate IQR results"],"whenToPreferThis":"Choose this endpoint when you need both category frequency analysis and IQR-based outlier detection specifically on transport ridership data (passenger_count and/or service_count fields) in a single low-cost call. It is ideal for offline batch-style statistical audits of up to 200 records without requiring any live data lookup, prediction, or external service. Prefer it over general analytics tools when working with the structured ridership schema (row_id, region, date) and needing a fast, cheap ($0.01 USDC) dual-report output.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:33:48.662Z","isFirstParty":false,"canonicalSlug":"transport-ridership-category-frequencies-iqr-outlier-flags-a3cce835"}