{"uid":"cap_bi_G57vI1M-qOuTY-SA7y","slug":"transport-ridership-category-frequencies-adjacent-row-changes-49a2fdc7","name":"Transport Ridership — Category Frequencies + Adjacent Row Changes","description":"Transport ridership — Category frequencies + Adjacent row changes: Category frequencies + Adjacent row changes 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-05-104?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_O0Sdy2UgZqrBrYWJ7-h0k","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":"Analyzes transport ridership data (passenger_count or service_count) by computing category frequencies and adjacent row changes for up to 200 rows.","exampleAgentPrompt":"Can you run a category frequency and adjacent row change analysis on my transport ridership data? I have 10 rows with region, date, passenger_count, and service_count fields — analyze passenger_count please.","exampleUseCases":[{"title":"Daily ridership trend detection","prompt":"I have a week's worth of daily ridership records across regions A, B, and C with passenger counts — can you show me how often each region appears and what the day-to-day changes in passenger_count look like?"},{"title":"Service count sequential delta report","prompt":"Here are 50 rows of transit service data with row IDs, dates, regions, and service_count values — run the category frequency and adjacent row change reports on service_count so I can see how service levels shift between consecutive entries."},{"title":"Multi-region ridership frequency audit","prompt":"I'm auditing ridership logs from five transit regions over the past month. Can you compute the category frequencies for each region and the row-by-row passenger_count changes across all 120 records?"}],"resultDescription":"Returns two independent analytical reports: (1) category frequencies showing how often each region (or other categorical field) appears across the supplied rows, and (2) adjacent row changes showing the delta in the chosen numeric field (passenger_count or service_count) between each consecutive row — all computed locally with no external lookups.","failureModes":["Exceeds 200-row limit — request rejected, must split into smaller batches","Missing required fields (row_id, region, date, passenger_count, service_count) — validation error","Invalid date format (must be YYYY-MM-DD) — schema validation failure","Field selector not one of allowed enum values (passenger_count, service_count) — rejected","Numeric values outside allowed range (-1e12 to 1e12) — schema error","Payment not attached or insufficient USDC — x402 payment required response"],"whenToPreferThis":"Choose this endpoint when you need two quick offline statistical reports — category frequency distributions and sequential row deltas — on transport ridership data with up to 200 rows. It is ideal when you already have the data locally and want lightweight batch analytics without any external API calls, predictions, or enrichment. Prefer it over general analytics platforms when cost predictability ($0.01 flat for both reports) and simplicity matter.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:32.393Z","isFirstParty":false,"canonicalSlug":"transport-ridership-category-frequencies-adjacent-row-changes-49a2fdc7"}