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Creating dummy variables

Being able to include categorical features in the model building process can enhance performance as they may add information that contributes to prediction accuracy.

The music_df dataset has been preloaded for you, and its shape is printed. Also, pandas has been imported as pd.

Now you will create a new DataFrame containing the original columns of music_df plus dummy variables from the "genre" column.

This exercise is part of the course

Supervised Learning with scikit-learn

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Exercise instructions

  • Use a relevant function, passing the entire music_df DataFrame, to create music_dummies, dropping the first binary column.
  • Print the shape of music_dummies.

Hands-on interactive exercise

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

# Create music_dummies
music_dummies = ____

# Print the new DataFrame's shape
print("Shape of music_dummies: {}".format(____))
Edit and Run Code