TypeError while using label encoder

Question

I am using the Beers dataset in which I want to encode the data with datatype 'object'. Following is my code.

from sklearn import preprocessing

df3 = BeerDF.select_dtypes(include=['object']).copy()

label_encoder = preprocessing.LabelEncoder()
df3 = df3.apply(label_encoder.fit_transform)

The following error is occurring.

TypeError: Encoders require their input to be uniformly strings or numbers. Got ['float', 'str']

Any insights are helpful!!!

Answer 1

Use:

df3 = df3.astype(str).apply(label_encoder.fit_transform)