Label encoding

Let's work on categorical variables encoding. You will again work with a subsample from the House Prices Kaggle competition.

Your objective is to encode categorical features "RoofStyle" and "CentralAir" using label encoding. The train and test DataFrames are already available in your workspace.

This exercise is part of the course

Winning a Kaggle Competition in Python

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Exercise instructions

Concatenate train and test DataFrames into a single DataFrame houses.
Create a LabelEncoder object without arguments and assign it to le.
Create new label-encoded features for "RoofStyle" and "CentralAir" using the same le object.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Concatenate train and test together
houses = ____.____([train, test])

# Label encoder
from sklearn.preprocessing import LabelEncoder
le = ____()

# Create new features
houses['RoofStyle_enc'] = le.fit_transform(houses[____])
houses['CentralAir_enc'] = ____.____(____[____])

# Look at new features
print(houses[['RoofStyle', 'RoofStyle_enc', 'CentralAir', 'CentralAir_enc']].head())

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