egutierrez
988e901066
Añade campos params y output al frontmatter YAML de las 506 funciones del registry. Cada parámetro tiene descripción semántica (qué representa, unidades, rango típico) y cada función describe qué produce su output. Permite a agentes razonar sobre cadenas de composición (ej: prices → log_return → sharpe_ratio) sin leer código.
1.0 KiB
1.0 KiB
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, params, output, 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 | params | output | tested | tests | test_file_path | file_path | ||||||||||||||
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| 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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lista de booleanos paralela a data, True donde |z-score| > threshold | 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.