{"uid":"cap_e2ibxaFlaQ29vAWWSOMWT","slug":"transport-ridership-base-100-series-missing-value-fill-5574d0c5","name":"Transport Ridership Base-100 Series & Missing-Value Fill","description":"Transport ridership — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill 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-05-169?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"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"},"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_b8j1nd_J2tgMmh-RYCd-g","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":"Computes a base-100 index series and fills missing values for transport ridership data (passenger_count or service_count) across up to 200 rows in two combined analytical reports.","exampleAgentPrompt":"Take my transit ridership records for regions group-a and group-b from October 2026 — up to 50 rows with passenger_count and service_count fields — and run the base-100 index series using row-1 as the base, filling any missing passenger_count values with the median.","exampleUseCases":[{"title":"Monthly ridership trend indexing","prompt":"I have 120 rows of monthly bus ridership data across 5 city regions from 2023 to 2024, some passenger_count values are null — can you normalize them to a base-100 series starting from row 0 and fill the missing values using median imputation?"},{"title":"Service count baseline comparison","prompt":"Here are 80 records of daily train service counts by region with some gaps — please compute a base-100 index anchored at row 5 and fill the missing service_count entries with zero so I can compare service levels across regions."},{"title":"Pandemic recovery ridership analysis","prompt":"I've got 200 rows of weekly subway passenger data covering the pandemic period with a lot of nulls — run the base-100 normalization from the first row using mean fill on passenger_count so I can see the recovery trend clearly."}],"resultDescription":"Returns two analytical reports for the supplied transport ridership dataset: (1) a base-100 index series where the specified base row equals 100 and all other rows are scaled relative to it, and (2) an explicit missing-value filled version of the chosen field (passenger_count or service_count) using the selected fill method (zero, mean, or median). Both reports use local analytical engines with no external data lookups.","failureModes":["Input array exceeds 200 rows — request rejected","Missing required fields (row_id, region, date) on any row causes validation error","Invalid date format (not YYYY-MM-DD) triggers schema rejection","base_index value pointing to a row index that doesn't exist in the submitted array","All values for the chosen field are null, making mean/median fill undefined","Payment of 0.01 USDC not completed — endpoint returns 402"],"whenToPreferThis":"Choose this endpoint when you have pre-collected transport ridership data (passenger counts or service counts) that needs to be normalized to a base-100 index for trend comparison and/or has missing values that need filling — all within a single low-cost call. Ideal for offline analytical pipelines processing up to 200 rows of transit data without needing live external data, predictions, or professional assessments.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:08.861Z","isFirstParty":false,"canonicalSlug":"transport-ridership-base-100-series-missing-value-fill-5574d0c5"}