{"uid":"cap_madVYo8nvq4VSPe7oiFTj","slug":"transport-ridership-grouped-numeric-summary-missing-value-fill-da8b530a","name":"Transport Ridership Grouped Numeric Summary + Missing-Value Fill","description":"Transport ridership — Grouped numeric summary + Explicit missing-value fill: Grouped numeric summary + 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-05-099?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"}}},"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_FKDB_g8keLhGdkRmjGi4j","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 grouped numeric summary statistics and fills missing values for transport ridership records (passenger_count, service_count) across up to 200 rows, returning 2 analytical reports.","exampleAgentPrompt":"I have ridership records for two regions with some missing passenger_count values — can you group them by region and compute summary stats, then fill the missing values using median imputation? Here's the data: row-1, group-a, 2026-10-01, passenger_count=10, service_count=1; row-2, group-b, 2026-10-02, passenger_count=null, service_count=2; row-3, group-a, 2026-10-03, passenger_count=15, service_count=3.","exampleUseCases":[{"title":"Monthly transit ridership summary by region","prompt":"I have 150 daily ridership records across 5 regions for October — can you group them by region and give me summary stats for passenger_count, and also fill in any missing passenger_count values using the median?"},{"title":"Impute missing service counts in bus data","prompt":"My bus operations dataset has some null service_count values. Can you fill those missing entries using the mean of available service_count values, and also give me a grouped numeric summary by region?"},{"title":"Validate and clean subway ridership export","prompt":"I exported subway ridership data with some blank passenger counts. Use zero-fill to replace the missing passenger_count values and compute grouped summary statistics by region so I can see totals and averages per area — there are about 80 rows total."}],"resultDescription":"Two analytical reports: (1) a grouped numeric summary of the specified field (e.g. passenger_count or service_count) broken down by region, including statistics such as count, mean, median, and sum; and (2) the input records with missing values in the specified field explicitly filled using the chosen method (zero, mean, or median).","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, region, date) causes rejection","Invalid date format (not YYYY-MM-DD) fails schema validation","Numeric values outside ±1,000,000,000,000 range are rejected","Empty rows array is not accepted (minItems: 1)","Invalid method or field enum value causes a schema error"],"whenToPreferThis":"Choose this endpoint when you have up to 200 transport ridership rows and need both grouped summary statistics and missing-value imputation in a single call. It is ideal for lightweight, offline analytical preprocessing of transit data (passenger counts, service counts) without requiring a full data pipeline or external database. Prefer it over generic analytics services when your data is already structured in the expected schema and you want two coordinated reports at minimal cost ($0.01 USDC).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:32:25.406Z","isFirstParty":false,"canonicalSlug":"transport-ridership-grouped-numeric-summary-missing-value-fill-da8b530a"}