{"uid":"cap_4BKePcT5--yuTpx8XXlpH","slug":"transport-ridership-iqr-outlier-flags-keyed-dataset-comparison-6f62b53c","name":"Transport Ridership IQR Outlier Flags + Keyed Dataset Comparison","description":"Transport ridership — IQR outlier flags + Keyed dataset comparison: IQR outlier flags + Keyed dataset comparison 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-05-179?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}$","maxLength":10},"region":{"type":"string","default":"","maxLength":80},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"service_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"passenger_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","region":"group-a","row_id":"row-1","service_count":1,"passenger_count":10},{"date":"2026-10-02","region":"group-b","row_id":"row-2","service_count":2,"passenger_count":20},{"date":"2026-10-03","region":"group-a","row_id":"row-3","service_count":3,"passenger_count":15},{"date":"2026-10-04","region":"group-b","row_id":"row-4","service_count":4,"passenger_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["passenger_count","service_count"],"type":"string","default":"passenger_count"},"other":{"type":"array","items":{"type":"object","required":["row_id","region","date","passenger_count","service_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","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":21},{"date":"2026-10-03","region":"group-a","row_id":"row-3","service_count":3,"passenger_count":17},{"date":"2026-10-04","region":"group-b","row_id":"row-4","service_count":4,"passenger_count":33}],"maxItems":200,"minItems":0}}},"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_ZkGv41pStu7vei2dikfi2","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 IQR-based outlier detection and keyed dataset comparison on up to 200 rows of transport ridership data (passenger_count or service_count), returning two independent analytical reports.","exampleAgentPrompt":"Can you check my transit ridership records for IQR outliers in passenger_count and also compare them against last month's dataset to flag any keyed differences? I have about 50 rows with region, date, row_id, passenger_count, and service_count.","exampleUseCases":[{"title":"Flagging anomalous daily ridership spikes","prompt":"I have 120 rows of daily bus ridership data with passenger_count and service_count by region — can you run IQR outlier detection on passenger_count and compare this week's data against last week's to see which row IDs changed significantly?"},{"title":"Transit data quality audit before reporting","prompt":"Before I submit our monthly transit report, can you check these 80 ridership records for IQR-based outliers in service_count and compare them against the baseline dataset I'm providing to catch any keyed discrepancies?"},{"title":"Comparing ridership across two route groups","prompt":"I've got two sets of ridership records — group-a and group-b routes, about 60 rows each — can you run an IQR outlier analysis on passenger_count and do a keyed comparison between the two datasets to see what's different?"}],"resultDescription":"Two independent analytical reports: (1) IQR outlier flags identifying which row IDs fall outside the interquartile range for the selected field (passenger_count or service_count), including the computed IQR boundaries; (2) a keyed dataset comparison report showing row-by-row differences between the primary and secondary (other) dataset, matched by row_id.","failureModes":["Fewer than 1 row submitted — validation error","More than 200 rows submitted — rejected with max items error","Missing required fields (row_id, region, date, passenger_count, service_count) — schema validation failure","Invalid date format (not YYYY-MM-DD) — pattern validation error","Numeric values outside allowed range (±1 trillion) — validation rejection","row_id not matched between primary and other datasets — keyed comparison may return empty or partial results","All values identical — IQR is zero, no outliers flagged"],"whenToPreferThis":"Choose this endpoint when you have transport ridership tabular data (up to 200 rows) and need both IQR statistical outlier detection and a keyed row-by-row comparison against a reference dataset in a single $0.01 call. It is purpose-built for transit/ridership domain data with passenger_count and service_count fields. Prefer this over generic statistical APIs when you want two bundled reports — outlier flags and dataset diff — without live data lookup, prediction, or external integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:32:37.423Z","isFirstParty":false,"canonicalSlug":"transport-ridership-iqr-outlier-flags-keyed-dataset-comparison-6f62b53c"}