egutierrez
63a9cb5273
Datascience: aggregate_by_group, deduplicate_entities/relations, detect_drift, diff_entities/relations, extract_entities/relations_llm, hotness_score, melt, merge_graphs, pivot, build_entity/relation_schema_prompt. Finance: avellaneda_stoikov_quotes, generate_gbm_prices, generate_taker_order, hawkes_intensity + módulo finance.py. Cybersecurity: envelope_encrypt/decrypt + módulo cybersecurity.py. Pipelines: extraction_pipeline, monte_carlo_market, run_market_sim. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
45 lines
1.4 KiB
Markdown
45 lines
1.4 KiB
Markdown
---
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name: pivot
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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 pivot(rows: list[dict], index: str, columns: str, values: str, agg: str = 'sum') -> list[dict]"
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description: "Pivot table sin pandas. Agrupa por index, expande valores unicos de columns como nuevas columnas y agrega values con la funcion indicada (sum, count, mean, min, max, first, last)."
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tags: [datascience, tabular, pivot, transform, aggregation, python]
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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: ["collections"]
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tested: true
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tests:
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- "Pivot basico con sum"
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- "Pivot con count y mean"
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- "Valores faltantes rellenados con 0"
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- "Una sola fila"
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- "Multiples valores por celda requieren agregacion"
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test_file_path: "python/functions/datascience/pivot_test.py"
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file_path: "python/functions/datascience/pivot.py"
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---
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## Ejemplo
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```python
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rows = [
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{"region": "US", "product": "A", "sales": 10},
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{"region": "US", "product": "B", "sales": 20},
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{"region": "EU", "product": "A", "sales": 15},
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]
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pivot(rows, index="region", columns="product", values="sales")
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# [{"region": "US", "A": 10, "B": 20}, {"region": "EU", "A": 15, "B": 0}]
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```
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## Notas
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Funcion pura sin dependencias externas (solo collections.defaultdict de stdlib).
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Preserva el orden de aparicion de los valores de index y columns.
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Valores numericos faltantes se rellenan con 0; no numericos con None.
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