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| # transformers.py | |
| from sklearn.base import BaseEstimator, TransformerMixin | |
| class SugarContentReplacer(BaseEstimator, TransformerMixin): | |
| def fit(self, X, y=None): | |
| return self | |
| def transform(self, X): | |
| X = X.copy() | |
| X['Product_Sugar_Content'] = X['Product_Sugar_Content'].replace('reg', 'Regular') | |
| return X | |
| def get_feature_names_out(self, input_features=None): | |
| if input_features is None: | |
| return ['Product_Sugar_Content'] | |
| else: | |
| return input_features | |
| ## | |
| class StoreAgeCalculator(BaseEstimator, TransformerMixin): | |
| def __init__(self): | |
| self.current_year = datetime.now().year | |
| def fit(self, X, y=None): | |
| return self | |
| def transform(self, X): | |
| X = X.copy() | |
| X['Store_Age'] = self.current_year - X['Store_Establishment_Year'] | |
| return X.drop(columns=['Store_Establishment_Year']) | |
| ## |