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| import pandas as pd | |
| import numpy as np | |
| import os | |
| def simulate_monthly_data(base_data_path, output_dir, months=12): | |
| # Create the output directory if it doesn't exist | |
| if not os.path.exists(output_dir): | |
| os.makedirs(output_dir) | |
| base_data = pd.read_csv(base_data_path) | |
| for month in range(1, months + 1): | |
| new_data = base_data.copy() | |
| drift_factor = np.random.normal(0, 0.1, new_data.shape) | |
| new_data += drift_factor | |
| new_data_path = os.path.join(output_dir, f'creditcard_month_{month}.csv') | |
| new_data.to_csv(new_data_path, index=False) | |
| print(f"Simulated data for month {month} saved to {new_data_path}") | |
| if __name__ == "__main__": | |
| simulate_monthly_data('C:/Fraud_Detection/creditcard.csv', 'C:/Fraud_Detection/simulated_data') | |
| #'C:/Fraud_Detection/creditcard.csv', |