Encoding categorical variables - binary

Take a look at the hiking dataset. There are several columns here that need encoding before they can be modeled, one of which is the Accessible column. Accessible is a binary feature, so it has two values, Y or N, which need to be encoded into 1's and 0's. Use scikit-learn's LabelEncoder method to perform this transformation.

This exercise is part of the course

Preprocessing for Machine Learning in Python

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Exercise instructions

Store LabelEncoder() in a variable named enc.
Using the encoder's .fit_transform() method, encode the hiking dataset's "Accessible" column. Call the new column Accessible_enc.
Compare the two columns side-by-side to see the encoding.

Hands-on interactive exercise

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

# Set up the LabelEncoder object
enc = ____

# Apply the encoding to the "Accessible" column
____ = ____.____(____)

# Compare the two columns
print(____[[____, ____]].head())

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