{"uid":"cap_W4PBRzuI2UaQusZowBwZv","slug":"transport-ridership-data-quality-suite-d00dbae5","name":"Transport Ridership Data Quality Suite","description":"Transport ridership — Record quality audit + Exact row deduplication + Trailing mean series: Record quality audit + Exact row deduplication + 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-05-216?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_4DvGo-_7OG_tOiazf8agJ","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 analytical reports on transport ridership records: record quality audit, exact row deduplication, and trailing mean series computation.","exampleAgentPrompt":"Can you audit my transit ridership data for quality issues, remove duplicate rows, and compute a trailing mean with window size 3 for passenger_count? Here are my records: region='north', date='2024-01-01', passenger_count=1200, service_count=40 (and a few more rows).","exampleUseCases":[{"title":"Monthly ridership data cleanup before reporting","prompt":"I have 150 rows of monthly bus ridership data with passenger_count and service_count fields and I need you to audit them for record quality issues, deduplicate any exact repeated rows, and compute a trailing mean over a window of 5 for passenger_count so I can prepare my monthly report."},{"title":"Detect anomalies in regional transit dataset","prompt":"Can you run a quality audit and deduplication check on my regional transit ridership records — about 80 rows covering regions like 'downtown' and 'suburbs' with dates from 2024-01-01 to 2024-03-31 — and also give me a trailing mean series with window 4 for service_count so I can spot anomalies?"},{"title":"Pre-analysis data validation for transit agency","prompt":"Before I run my ridership analysis, can you check this dataset of 60 rows for data quality issues, find and flag any exact duplicate records, and calculate a rolling average with window size 2 on passenger_count? The rows include row_id, region, date, passenger_count, and service_count fields."}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging nulls, out-of-range values, and format issues per row; (2) an exact row deduplication report identifying and grouping identical records; (3) a trailing mean series for the selected numeric field (passenger_count or service_count) using the specified window size — all computed locally from the supplied data, covering up to 200 rows.","failureModes":["More than 200 rows submitted — request rejected with validation error","Missing required fields (row_id, region, date, passenger_count, or service_count) — schema validation failure","Invalid date format not matching YYYY-MM-DD pattern — rejected","Window size outside range 2–200 — validation error","Empty rows array — minimum 1 item required","Numeric values outside allowed range (-1e12 to 1e12) — rejected"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical operations on transport ridership data (quality audit, deduplication, and trailing mean) in a single low-cost call. Ideal for preprocessing transit datasets of up to 200 rows before visualization or modeling. Prefer this over generic data tools when your data specifically includes passenger_count and service_count fields and you need all three reports simultaneously without any external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:18.814Z","isFirstParty":false,"canonicalSlug":"transport-ridership-data-quality-suite-d00dbae5"}