{"uid":"cap_GH5Bkug1xWAT2ol3UWSCm","slug":"wind-observations-numeric-row-ordering-missing-value-fill-580a0aa4","name":"Wind Observations – Numeric Row Ordering & Missing-Value Fill","description":"Wind observations — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied wind observations records (wind_speed_ms, gust_speed_ms). 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-weather-03-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","station_group","date","wind_speed_ms","gust_speed_ms"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"gust_speed_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"station_group":{"type":"string","default":"","maxLength":80},"wind_speed_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","gust_speed_ms":1,"station_group":"group-a","wind_speed_ms":10},{"date":"2026-10-02","row_id":"row-2","gust_speed_ms":2,"station_group":"group-b","wind_speed_ms":20},{"date":"2026-10-03","row_id":"row-3","gust_speed_ms":3,"station_group":"group-a","wind_speed_ms":15},{"date":"2026-10-04","row_id":"row-4","gust_speed_ms":4,"station_group":"group-b","wind_speed_ms":30}],"maxItems":200,"minItems":1},"field":{"enum":["wind_speed_ms","gust_speed_ms"],"type":"string","default":"wind_speed_ms"},"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_00UH-P_oAis6bVwZBVufz","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":"Sorts wind observation records numerically by row and fills missing wind_speed_ms or gust_speed_ms values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have up to 50 wind observation records with some missing gust_speed_ms values — can you sort them numerically by row and fill in the missing gust speed values using median imputation, then give me the two analytical reports?","exampleUseCases":[{"title":"Clean wind dataset before ML pipeline","prompt":"I have 120 wind station records grouped by station_group with some null wind_speed_ms entries. Please sort them by row number and fill the missing wind speeds using median imputation so I can feed the cleaned data into my model."},{"title":"Impute missing gusts with zero fill","prompt":"My anemometer data has about 30 rows and several null gust_speed_ms readings. Can you order the rows numerically and fill all the missing gust speed values with zero, then return the two reports?"},{"title":"Audit and order multi-station wind logs","prompt":"I've got wind observations from two station groups across 80 dates and there are some gaps in wind_speed_ms. Sort everything numerically by row ID and use mean imputation to fill the missing wind speeds — I need both analytical reports back."}],"resultDescription":"Two analytical reports covering the supplied wind observation records after numeric row ordering and explicit missing-value fill. Each report reflects the sorted, imputed dataset for the chosen field (wind_speed_ms or gust_speed_ms) using the specified fill method (zero, mean, or median). No live data or external lookups are performed.","failureModes":["More than 200 rows submitted — request exceeds maxItems limit","Invalid date format — must match YYYY-MM-DD pattern","Missing required row fields (row_id, station_group, date)","Invalid enum value for method or field parameter","Empty rows array — minItems is 1","Numeric values outside allowed range (±1,000,000,000,000)"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 wind observation records that need deterministic numeric row ordering and missing-value imputation (zero, mean, or median) with no need for live weather data, forecasts, or external lookups. Ideal for data preparation pipelines where reproducibility and offline computation matter, and when two structured analytical reports per call are sufficient.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:40:28.504Z","isFirstParty":false,"canonicalSlug":"wind-observations-numeric-row-ordering-missing-value-fill-580a0aa4"}