Use ColumnTransformer to apply different preprocessing to different columns in ONE go.

Use ColumnTransformer to apply different preprocessing to different columns.py

import pandas as pd
df = pd.read_csv('http://bit.ly/kaggletrain', nrows=6)

cols = ['Fare', 'Embarked', 'Sex', 'Age']
X = df[cols]

from sklearn.preprocessing import OneHotEncoder
from sklearn.impute import SimpleImputer
from sklearn.compose import make_column_transformer

oneHotEncoder = OneHotEncoder()
imputer = SimpleImputer()

column_transformer = make_column_transformer(
    (oneHotEncoder, ['Embarked', 'Sex']),  # Apply OneHotEncoder to Embarked and Sex
    (imputer, ['Age']),              # Apply SimpleImputer to Age
    remainder='passthrough')     # Include remaining column (Fare) in the output

# Column order: Embarked (3 columns), Sex (2 columns), Age (1 column), Fare (1 column)
column_transformer.fit_transform(X)