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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.

Latihan ini adalah bagian dari kursus

Winning a Kaggle Competition in Python

Lihat Kursus

Petunjuk latihan

  • 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.

Latihan interaktif praktis

Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# 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())
Edit dan Jalankan Kode