{"uid":"cap_BfIWoD5YwZ_pO4gpq4lOw","slug":"simulation-caches-numeric-row-ordering-explicit-missing-value-fill-f1631524","name":"Simulation Caches — Numeric Row Ordering + Explicit Missing-Value Fill","description":"Simulation caches — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied simulation caches records (cache_gb, simulation_seconds). 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-creative-08-124?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","cache_gb","simulation_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"cache_gb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"simulation_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","cache_gb":10,"asset_group":"group-a","simulation_seconds":1},{"date":"2026-10-02","row_id":"row-2","cache_gb":20,"asset_group":"group-b","simulation_seconds":2},{"date":"2026-10-03","row_id":"row-3","cache_gb":15,"asset_group":"group-a","simulation_seconds":3},{"date":"2026-10-04","row_id":"row-4","cache_gb":30,"asset_group":"group-b","simulation_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["cache_gb","simulation_seconds"],"type":"string","default":"cache_gb"},"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_rlYl6E6vob1j6-Hms5hVv","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 simulation cache records numerically by row and fills missing cache_gb or simulation_seconds values using zero, mean, or median imputation, delivering two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have simulation cache records with some missing cache_gb values — can you sort them numerically by row and fill those gaps using median imputation? Here are up to 200 rows with fields row_id, asset_group, date, cache_gb, and simulation_seconds.","exampleUseCases":[{"title":"Clean missing cache sizes before reporting","prompt":"I have 150 rows of simulation cache data and some cache_gb entries are null — sort everything by row number and fill the missing cache_gb values using the median so I can produce a clean report."},{"title":"Impute simulation run times with mean fill","prompt":"My simulation_seconds column has several nulls across about 80 rows — can you order the rows numerically and fill in those missing simulation_seconds values using the mean of the available ones?"},{"title":"Zero-fill gaps in asset group cache data","prompt":"I've got simulation cache records grouped by asset_group with some blank cache_gb entries — sort them in row order and replace all the missing values with zero so the dataset is complete."}],"resultDescription":"Two analytical reports covering the submitted simulation cache records: one showing rows sorted in numeric order and one showing the dataset with missing values in the selected field (cache_gb or simulation_seconds) explicitly filled using the chosen method (zero, mean, or median). Up to 200 rows are processed per call using local analytical engines with no external data lookups.","failureModes":["Rows array is empty or missing — validation error returned","More than 200 rows submitted — request rejected","Invalid date format (not YYYY-MM-DD) on a row — schema validation failure","Unrecognized fill method or field enum value — bad request error","All values in selected field are null — mean/median fill may be undefined or return zero","row_id missing or empty string — schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously sort simulation cache records by numeric row order AND impute missing numeric values in cache_gb or simulation_seconds in a single low-cost call. It is ideal for preprocessing simulation performance datasets before aggregation or reporting, especially when null handling strategy (zero, mean, or median) needs to be explicit. Prefer it over generic data tools when your data fits the simulation cache schema (asset_group, date, cache_gb, simulation_seconds) and you want two bundled analytical outputs for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-22T00:49:23.326Z","isFirstParty":false,"canonicalSlug":"simulation-caches-numeric-row-ordering-explicit-missing-value-fill-f1631524"}