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

If you have all the features of type object then the first answer written above works well https://stackoverflow.com/a/31939145/5840973.

But, Suppose when we have mixed type columns. Then we can fetch the list of features names of type object type programmatically and then Label Encode them.

#Fetch features of type Object
objFeatures = dataframe.select_dtypes(include="object").columns

#Iterate a loop for features of type object
from sklearn import preprocessing
le = preprocessing.LabelEncoder()

for feat in objFeatures:
    dataframe[feat] = le.fit_transform(dataframe[feat].astype(str))
 

dataframe.info()