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.

Este exercício faz parte do curso

Winning a Kaggle Competition in Python

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Instruções do exercício

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.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# 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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