egutierrez
fc734029c1
12 funciones puras con implementación real: Standardize, MinMaxScale, Clip, RollingWindow, ZipSlices, GroupBy, Histogram, Pearson, Autocorrelation, FFT (Cooley-Tukey), DetectOutliers, Impute 3 funciones impuras (stubs): LoadCSV, LoadParquet, FetchDataFrame Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
560 B
560 B
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, tested, tests, test_file_path, file_path
| name | kind | lang | domain | version | purity | signature | description | tags | uses_functions | uses_types | returns | returns_optional | error_type | imports | tested | tests | test_file_path | file_path | |||||
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| detect_outliers | function | go | datascience | 1.0.0 | pure | func DetectOutliers(data []float64, threshold float64) []bool | Detecta outliers en un slice de float64 usando z-score. Devuelve true para valores cuyo |z-score| supera el umbral. |
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false |
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false | functions/datascience/detect_outliers.go |