Created
May 18, 2025 10:01
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| import pandas as pd | |
| import numpy as np | |
| from tqdm import tqdm | |
| # 1. Генерация тестовой таблицы (1 000 000 строк) | |
| def generate_test_data(rows=1000000): | |
| data = { | |
| 'id': np.arange(1, rows+1), | |
| 'value': np.random.rand(rows) * 100, | |
| 'category': np.random.choice(['A', 'B', 'C', 'D'], size=rows) | |
| } | |
| return pd.DataFrame(data) | |
| # 2. Функция обработки с прогресс-баром | |
| def process_data(df): | |
| # Включаем прогресс-бар для apply | |
| tqdm.pandas(desc="Обработка строк") | |
| # Вычисления | |
| print('Возведение в квадрат') | |
| df['squared'] = round(df['value'].progress_apply(lambda x: x**2), 2) | |
| print() | |
| print('Возведение в куб') | |
| df['cubing '] = round(df['value'].progress_apply(lambda x: x**3), 2) | |
| print() | |
| print('Извлечение квадратного корня') | |
| df['sqrt '] = round(df['value'].progress_apply(lambda x: np.sqrt(x)), 2) | |
| return df | |
| # Генерируем данные | |
| df = generate_test_data() | |
| # Обрабатываем с прогресс-баром | |
| result = process_data(df) | |
| print() | |
| print('Итоговая таблица') | |
| display(result) |
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