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| # utils/feature_engineering.py | |
| import pandas as pd | |
| import numpy as np | |
| def feature_engineering(df): | |
| df['hour_of_day'] = pd.to_datetime(df['timestamp']).dt.hour | |
| df['day_of_week'] = pd.to_datetime(df['timestamp']).dt.dayofweek | |
| df['amount_times_hour'] = df['amount'] * df['hour_of_day'] | |
| df['log_amount'] = df['amount'].apply(lambda x: 0 if x == 0 else np.log(x + 1)) | |
| df = df.drop(['timestamp', 'amount'], axis=1) | |
| return df | |