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, kursun bir parçasıdır
Winning a Kaggle Competition in Python
Egzersiz 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 etkileşimli egzersiz
Bu egzersizi bu örnek kodu tamamlayarak deneyin.
# 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())