eaed99e52c
Agrega funciones Python reutilizables organizadas por dominio: - core: composicion funcional (pipe, compose, map, filter, reduce, etc.) - cybersecurity: analisis de amenazas y puertos - datascience: estadisticas y deteccion de outliers - finance: indicadores tecnicos y analisis financiero
738 B
738 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 | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| detect_outliers | function | py | datascience | 1.0.0 | pure | def detect_outliers(data: list, threshold: float) -> list | Detecta outliers por z-score. Retorna lista de bools, True donde |z-score| > threshold. |
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false |
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false | python/functions/datascience/datascience.py |
Ejemplo
detect_outliers([1, 2, 3, 100, 2, 3], 2.0)
# [False, False, False, True, False, False]
Notas
Usa z-score poblacional. Threshold tipico: 2.0 o 3.0. Si la desviacion es cero, no hay outliers.