{"uid":"cap__T6fjDPsvjozIXx8EcKqc","slug":"transport-ridership-numeric-row-ordering-base-100-series-dec27349","name":"Transport Ridership — Numeric Row Ordering + Base-100 Series","description":"Transport ridership — Numeric row ordering + Base-100 series: Numeric row ordering + Base-100 series 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-05-117?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":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_O4ivdcxUFYCozBuNUynyf","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":"Assigns numeric row ordering and computes a Base-100 index series for passenger_count or service_count across up to 200 transport ridership records, returning two analytical reports.","exampleAgentPrompt":"Can you run a numeric row ordering and Base-100 index series on my transit ridership data? I have 4 rows with passenger_count values across two regions (group-a and group-b) from October 2026, and I want the indexing to start from row 0 (base_index=0), using passenger_count as the field.","exampleUseCases":[{"title":"Monthly ridership growth indexing","prompt":"I have 12 months of bus ridership data for three city regions — can you order the rows numerically and build a Base-100 series on passenger_count starting from January (base_index 0) so I can see how ridership has grown relative to that baseline?"},{"title":"Service frequency baseline comparison","prompt":"I want to compare how service counts have changed across my transit routes over the past quarter — can you run the numeric row ordering and Base-100 index on service_count for my 50 rows of route data, anchoring the index at row 0?"},{"title":"Regional ridership trend normalization","prompt":"I have ridership records for 5 different metro regions and I need to normalize passenger_count to a Base-100 series so I can compare trends across regions on the same scale — can you process all 80 rows starting the index at row 0?"}],"resultDescription":"Returns two analytical reports: (1) a numeric row ordering of the submitted ridership records, and (2) a Base-100 index series computed on the selected field (passenger_count or service_count), where the row at base_index is set to 100 and all other rows are expressed relative to it. Results are derived entirely from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, region, date, passenger_count, service_count) causes rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","base_index out of range (0–199) causes error","Null values in the selected field may affect Base-100 calculation accuracy","Submitting zero rows fails minItems constraint"],"whenToPreferThis":"Choose this endpoint when you need to both sequence transport ridership records by row order AND produce a Base-100 normalized index series in a single API call. It is ideal for transit analysts who want to compare ridership or service trends relative to a starting baseline without building their own indexing logic. Prefer it over general analytics tools when working specifically with passenger_count and service_count data up to 200 rows and needing two bundled reports at a fixed low cost.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:17.588Z","isFirstParty":false,"canonicalSlug":"transport-ridership-numeric-row-ordering-base-100-series-dec27349"}