| from sklearn.model_selection import train_test_split | |
| def split_data(df, target_col, test_size=0.2, random_state=42): | |
| X = df.drop(columns=[target_col]) | |
| y = df[target_col] | |
| return train_test_split(X, y, test_size=test_size, random_state=random_state) | |
| from sklearn.model_selection import train_test_split | |
| def split_data(df, target_col, test_size=0.2, random_state=42): | |
| X = df.drop(columns=[target_col]) | |
| y = df[target_col] | |
| return train_test_split(X, y, test_size=test_size, random_state=random_state) | |