import pandas as pd
import numpy as np

np.random.seed(42)

n = 1_000_000

regions = ['north', 'south', 'east', 'west']
categories = ['electronics', 'clothing', 'furniture', 'food', 'sports']
statuses = ['completed', 'returned', 'pending', 'cancelled']

df = pd.DataFrame({
    'order_id': np.arange(1000, 1000 + n),
    'order_date': pd.date_range(start='2022-01-01', periods=n, freq='1min'),
    'region': np.random.choice(regions, size=n),
    'category': np.random.choice(categories, size=n),
    'sales': np.random.randint(100, 10000, size=n),
    'quantity': np.random.randint(1, 20, size=n),
    'discount': np.round(np.random.uniform(0.0, 0.5, size=n), 2),
    'status': np.random.choice(statuses, size=n),
})

df.to_csv('large_sales_data.csv', index=False)