Combining sparse class

categorical_features=[feature for feature in dataset.columns if dataset[feature].dtype=='O']
for feature in categorical_features:   
    temp=dataset[feature].value_counts(normalize=True)
    temp_df=temp[temp>0.01].index                     
    
    dataset[feature]=np.where(dataset[feature].isin(temp_df),dataset[feature],'Rare_var')
                                   # condition satisfies then   'X'            else'Y'
                                   #condition---------->   ,take this values else,'Rare_var'

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