Label encoding across multiple columns in scikit-learn

Question

I\'m trying to use scikit-learn\'s LabelEncoder to encode a pandas DataFrame of string labels. As the dataframe has many (50+) columns, I want to a

Answer 1

How about this?

def MultiColumnLabelEncode(choice, columns, X):
    LabelEncoders = []
    if choice == 'encode':
        for i in enumerate(columns):
            LabelEncoders.append(LabelEncoder())
        i=0    
        for cols in columns:
            X[:, cols] = LabelEncoders[i].fit_transform(X[:, cols])
            i += 1
    elif choice == 'decode': 
        for cols in columns:
            X[:, cols] = LabelEncoders[i].inverse_transform(X[:, cols])
            i += 1
    else:
        print('Please select correct parameter "choice". Available parameters: encode/decode')

It is not the most efficient, however it works and it is super simple.