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- .claude/CLAUDE.md - .claude/commands/subagentes.md - .claude/rules/INDEX.md - .mcp.json - bash/functions/cybersecurity/analyze_dns.md - bash/functions/cybersecurity/audit_http_headers.md - bash/functions/cybersecurity/audit_ssh_config.md - bash/functions/cybersecurity/check_firewall.md - bash/functions/cybersecurity/detect_suspicious_users.md - bash/functions/cybersecurity/encrypt_file.md - ... Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
37 lines
866 B
Markdown
37 lines
866 B
Markdown
---
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name: impute
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kind: function
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lang: py
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domain: datascience
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version: "1.0.0"
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purity: pure
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signature: "def impute(data: list) -> list"
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description: "Reemplaza None y NaN con la media de los valores validos."
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tags: [imputation, missing, python, pendiente-usar]
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uses_functions: []
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uses_types: []
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returns: []
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returns_optional: false
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error_type: ""
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imports: [math]
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params:
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- name: data
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desc: "lista de valores numericos con posibles None o NaN que requieren imputacion"
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output: "lista de misma longitud con None y NaN reemplazados por la media de los valores validos"
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tested: false
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tests: []
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test_file_path: ""
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file_path: "python/functions/datascience/datascience.py"
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---
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## Ejemplo
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```python
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impute([1.0, None, 3.0, float('nan'), 5.0])
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# [1.0, 3.0, 3.0, 3.0, 5.0]
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```
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## Notas
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Detecta tanto None como float('nan'). Si no hay valores validos, rellena con 0.0.
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