Understanding the components
You'll apply PCA to the numeric features of the Pokemon dataset, poke_df, using a pipeline to combine the feature scaling and PCA in one go. You'll then interpret the meanings of the first two components.
All relevant packages and classes have been pre-loaded for you (Pipeline(), StandardScaler(), PCA()).
This exercise is part of the course
Dimensionality Reduction in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Build the pipeline
pipe = Pipeline([('scaler', ____),
('reducer', ____(____))])