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.
Bu egzersiz
Winning a Kaggle Competition in Python
kursunun bir parçasıdırEgzersiz talimatları
- Concatenate
trainandtestDataFrames into a single DataFramehouses. - Create a
LabelEncoderobject without arguments and assign it tole. - Create new label-encoded features for "RoofStyle" and "CentralAir" using the same
leobject.
Uygulamalı interaktif egzersiz
Bu örnek kodu tamamlayarak bu egzersizi bitirin.
# 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())