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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

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Build the pipeline
pipe = Pipeline([('scaler', ____),
        		 ('reducer', ____(____))])
Edit and Run Code