How to reverse Label Encoder from sklearn for multiple columns?

Question

I would like to use the inverse_transform function for LabelEncoder on multiple columns.

This is the code I use for more than one columns when applying LabelEncoder

Answer 1

You do not need to modify it this way. It's already implemented as a method inverse_transform.

Example:

from sklearn import preprocessing

le = preprocessing.LabelEncoder()
df = ["paris", "paris", "tokyo", "amsterdam"]

le_fitted = le.fit_transform(df)

inverted = le.inverse_transform(le_fitted)

print(inverted)
# array(['paris', 'paris', 'tokyo', 'amsterdam'], dtype='|S9')