egutierrez
837563c3ba
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>
1.4 KiB
1.4 KiB
name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, 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 | tested | tests | test_file_path | file_path | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| pivot | function | py | datascience | 1.0.0 | pure | def pivot(rows: list[dict], index: str, columns: str, values: str, agg: str = 'sum') -> list[dict] | 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). |
|
false |
|
true |
|
python/functions/datascience/pivot_test.py | python/functions/datascience/pivot.py |
Ejemplo
rows = [
{"region": "US", "product": "A", "sales": 10},
{"region": "US", "product": "B", "sales": 20},
{"region": "EU", "product": "A", "sales": 15},
]
pivot(rows, index="region", columns="product", values="sales")
# [{"region": "US", "A": 10, "B": 20}, {"region": "EU", "A": 15, "B": 0}]
Notas
Funcion pura sin dependencias externas (solo collections.defaultdict de stdlib). Preserva el orden de aparicion de los valores de index y columns. Valores numericos faltantes se rellenan con 0; no numericos con None.