{"uid":"cap_O-SFPVXN8xYKeWxY61P8y","slug":"transport-ridership-string-normalisation-and-numeric-row-ordering-c1d19858","name":"Transport Ridership String Normalisation and Numeric Row Ordering","description":"Transport ridership — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering 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-05-025?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_oxlytYlmJntK1Pk3ZRtkL","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":"Normalises region/date strings and sorts transport ridership rows by passenger_count or service_count for up to 200 supplied records, returning two analytical reports.","exampleAgentPrompt":"Can you normalise the region names and sort these transport ridership records by passenger_count? I have 4 rows: row-1 group-a 2026-10-01 passengers=10 services=1, row-2 group-b 2026-10-02 passengers=20 services=2, row-3 group-a 2026-10-03 passengers=15 services=3, row-4 group-b 2026-10-04 passengers=30 services=4 — I need the two standard analytical reports.","exampleUseCases":[{"title":"Rank bus routes by daily ridership","prompt":"I have daily ridership records for 50 bus routes across different regions — can you normalise the region labels and sort all the rows by passenger_count so I can see which routes are busiest?"},{"title":"Sort transit service data by frequency","prompt":"Here are 120 rows of transit service records with region names that need cleaning up — please normalise the strings and order the rows by service_count, and give me both analytical reports."},{"title":"Clean and order monthly transit snapshot","prompt":"I've got a monthly transport ridership snapshot with messy region naming across 80 records — normalise those strings and rank the rows by passenger_count so I can hand the ordered data to my planning team."}],"resultDescription":"Two analytical reports covering: (1) normalised string values for the region and date fields across all supplied rows, and (2) the rows reordered numerically by the selected field (passenger_count or service_count). No external data is fetched; all processing is local to the supplied rows.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds limit","row_id missing or empty — schema validation error","date field not in YYYY-MM-DD format — pattern validation error","Numeric values outside ±1,000,000,000,000 range — schema rejection","field enum value not 'passenger_count' or 'service_count' — validation error"],"whenToPreferThis":"Choose this endpoint when you need to both clean/normalise string fields (region, date) and numerically sort transport ridership rows (by passenger or service count) in a single call, receiving two bundled reports. It is well-suited for small-to-medium datasets (up to 200 rows) where no live data lookup, prediction, or external action is needed — just local analytical processing on data you supply.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:47.589Z","isFirstParty":false,"canonicalSlug":"transport-ridership-string-normalisation-and-numeric-row-ordering-c1d19858"}