{"uid":"cap_2mBNHl2ThmX7vbHPTvH7l","slug":"transport-ridership-data-quality-audit-string-normalisation-trailing-7ee42553","name":"Transport Ridership Data Quality Audit, String Normalisation & Trailing Mean Series","description":"Transport ridership — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series 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-05-199?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_UayDgYjQxsZR3UMChF-I_","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":"Performs three bundled analytical reports on transport ridership records: record quality audit, string normalisation, and trailing mean time-series computation for passenger_count or service_count.","exampleAgentPrompt":"Can you audit the data quality, normalise the region strings, and compute a 7-day trailing mean on passenger_count for these 150 rows of bus ridership data I have? Here are the rows with row_id, region, date, passenger_count, and service_count.","exampleUseCases":[{"title":"Pre-load ridership data QA check","prompt":"Before I load this month's bus ridership records into our dashboard, can you run a full quality audit on these 120 rows checking passenger_count and service_count for issues, normalise the region names, and compute a trailing mean over a window of 5 for passenger_count?"},{"title":"Rolling average for transit planning","prompt":"I've got 90 rows of daily subway ridership data with region, date, passenger_count, and service_count — can you calculate a 14-period trailing mean on service_count so I can see the smoothed trend over time?"},{"title":"Cleaning messy region labels in transit exports","prompt":"Our transit export has inconsistent capitalisation and spacing in the region field across 60 rows — can you run the string normalisation report on these records along with the quality audit so I can see what needs fixing?"}],"resultDescription":"Returns three independent reports: (1) a record quality audit flagging nulls, out-of-range values, and structural issues in passenger_count and service_count; (2) a string normalisation report on region values; and (3) a trailing mean time series for the chosen field (passenger_count or service_count) computed over the specified window size. All reports are generated locally without external lookups.","failureModes":["Exceeds 200 row limit — request rejected","Missing required fields (row_id, region, date, passenger_count, or service_count) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Window size outside allowed range (2–200) — parameter error","All numeric values null — trailing mean series may be empty or undefined"],"whenToPreferThis":"Choose this endpoint when you need three combined analytical operations on transport ridership data (audit + normalisation + trailing mean) in a single low-cost call. Ideal for pre-ingestion data pipeline checks on datasets up to 200 rows. Best suited when no live data lookup, prediction, or external enrichment is needed — purely local analysis on supplied records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T00:44:06.147Z","isFirstParty":false,"canonicalSlug":"transport-ridership-data-quality-audit-string-normalisation-trailing-7ee42553"}