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python
24 days ago
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from sklearn.impute import KNNImputer # Select numerical features numerical_features = df.select_dtypes(include=['int64', 'float64']) # Initialize KNNImputer for numerical features imputer_num = KNNImputer(n_neighbors=5) # Set the desired value of k # Impute missing values for numerical features df[numerical_features.columns] = imputer_num.fit_transform(numerical_features)