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
Exercise instructions
- Concatenate
train
andtest
DataFrames into a single DataFramehouses
. - Create a
LabelEncoder
object without arguments and assign it tole
. - 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())