{"uid":"cap_YSgxlnHc1gGkG4lOdPj09","slug":"transport-ridership-record-quality-audit-string-normalisation-numeric-c3ff4cf3","name":"Transport Ridership Record Quality Audit + String Normalisation + Numeric Distribution","description":"Transport ridership — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied transport ridership records (passenger_count, service_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-economics-05-193?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_8vFNVq-FFpXnreSRNAKZe","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 three local analytical reports on supplied transport ridership data: a record quality audit, string normalisation, and numeric distribution analysis for passenger_count or service_count fields.","exampleAgentPrompt":"Can you audit the quality of these transport ridership records, normalise the region strings, and give me a numeric distribution for passenger_count? I have about 50 rows with fields row_id, region, date, passenger_count, and service_count.","exampleUseCases":[{"title":"Pre-load ridership data audit","prompt":"Before I load my transit dataset into the warehouse, can you run a record quality audit, normalise the region name strings, and show me the numeric distribution of passenger_count for these 120 ridership rows?"},{"title":"Service count distribution analysis","prompt":"I have 80 rows of bus service data with region, date, and service_count fields — can you give me a numeric distribution of service_count and flag any quality issues in the records?"},{"title":"Regional string cleanup in ridership data","prompt":"My ridership export has inconsistent region labels — can you normalise those strings, audit overall record quality, and profile the passenger_count distribution across these 45 rows?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging missing values, type errors, and constraint violations; (2) a string normalisation report showing standardised region values; and (3) a numeric distribution summary (min, max, mean, percentiles, histogram bins, etc.) for the selected numeric field — all computed locally on the supplied rows, no external lookups.","failureModes":["Payload exceeds 200 rows — request rejected","Missing required fields (row_id, region, date, passenger_count, service_count) causes validation error","Invalid date format (not YYYY-MM-DD) triggers schema rejection","Numeric values outside ±1,000,000,000,000 bounds rejected","Empty rows array returns error","Payment of 0.01 USDC not completed — 402 response blocks execution"],"whenToPreferThis":"Choose this endpoint when you need three simultaneous data-profiling reports (quality audit, string normalisation, and numeric distribution) on transport ridership records in a single cost-efficient call. It is best suited for pre-ingestion validation, data cleaning pipelines, and exploratory profiling of up to 200 ridership rows without requiring external data access or live lookups. Prefer it over general-purpose analytics when your data specifically includes passenger_count and service_count fields alongside region and date dimensions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:07.281Z","isFirstParty":false,"canonicalSlug":"transport-ridership-record-quality-audit-string-normalisation-numeric-c3ff4cf3"}