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import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from sklearn.compose import make_column_transformer
import sklearn

print(sklearn.__version__) # 0.22.2.post1

df = sns.load_dataset('titanic').head()

le = OneHotEncoder() # this success
# le = LabelEncoder() # this fails

ct = make_column_transformer(
(le, ['sex','adult_male','alone']),
remainder='drop')

ct.fit_transform(df)