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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>
53 lines
1.9 KiB
Markdown
53 lines
1.9 KiB
Markdown
---
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name: melt
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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 melt(rows: list[dict], id_vars: list[str], value_vars: list[str] | None = None, var_name: str = 'variable', value_name: str = 'value') -> list[dict]"
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description: "Inversa de pivot. Convierte columnas en filas (formato largo). Cada combinacion de id_vars + value_var genera una fila. Si value_vars es None, derrite todas las columnas no-id."
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tags: [datascience, tabular, melt, unpivot, transform, 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: []
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params:
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- name: rows
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desc: "lista de dicts en formato ancho (ej: [{'region': 'US', 'q1': 10, 'q2': 20}])"
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- name: id_vars
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desc: "lista de columnas a mantener como identificadores (ej: ['region']). No se derriten."
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- name: value_vars
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desc: "lista de columnas a derretir (ej: ['q1', 'q2']). Si None, derrite todas excepto id_vars."
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- name: var_name
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desc: "nombre de la columna que contendra los nombres de columnas derretidas (defecto: 'variable')"
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- name: value_name
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desc: "nombre de la columna que contendra los valores (defecto: 'value')"
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output: "lista de dicts en formato largo, donde cada id_var + value_var genera una fila"
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tested: true
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tests:
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- "Melt basico"
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- "Multiples id_vars"
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- "value_vars None derrite todas las columnas no-id"
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- "Fila con campo faltante en value_vars"
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test_file_path: "python/functions/datascience/melt_test.py"
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file_path: "python/functions/datascience/melt.py"
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---
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## Ejemplo
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```python
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rows = [{"region": "US", "q1": 10, "q2": 20}]
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melt(rows, id_vars=["region"], value_vars=["q1", "q2"])
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# [{"region": "US", "variable": "q1", "value": 10},
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# {"region": "US", "variable": "q2", "value": 20}]
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```
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## Notas
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Funcion pura sin dependencias externas.
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Si un campo de value_vars no existe en la fila, su valor sera None.
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El parametro value_vars=None es util cuando se desconoce el schema exacto.
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