Files
egutierrez a03675113a chore: auto-commit (286 archivos)
- .claude/agents/fn-orquestador/SKILL.md
- .claude/commands/fn_claude.md
- .claude/rules/INDEX.md
- .claude/rules/cpp_apps.md
- .claude/rules/ids_naming.md
- CHANGELOG.md
- apps/dag_engine/README.md
- apps/dag_engine/api.go
- apps/dag_engine/dags_migrated/example.yaml
- apps/dag_engine/dags_migrated/example_lineage_tracking.yaml
- ...

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-16 16:33:22 +02:00

879 B

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
impute function py datascience 1.0.0 pure def impute(data: list) -> list Reemplaza None y NaN con la media de los valores validos.
imputation
missing
python
pendiente-usar
transformer
false
math
name desc
data lista de valores numericos con posibles None o NaN que requieren imputacion
lista de misma longitud con None y NaN reemplazados por la media de los valores validos false
python/functions/datascience/datascience.py

Ejemplo

impute([1.0, None, 3.0, float('nan'), 5.0])
# [1.0, 3.0, 3.0, 3.0, 5.0]

Notas

Detecta tanto None como float('nan'). Si no hay valores validos, rellena con 0.0.