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A first look

Using the full Avazu dataset, you will explore various new features by looking at the data types of columns. The new data includes categorical columns such as site_id, app_id, device_id, etc. all of which are various identifiers for a given site, app, and user respectively. To start off, you will identify and print out the numerical and categorical columns.

Sample data in DataFrame form is loaded as df. pandas as pd is also available in your workspace.

This exercise is part of the course

Predicting CTR with Machine Learning in Python

View Course

Exercise instructions

  • Print the columns of df using .columns.
  • Print the corresponding data types of df using .dtypes.
  • Select the subset of df with numerical columns (by using include = ['int', 'float']) and print those columns.
  • Select the subset of df with categorical columns (by using include = ['object']) and print those columns.

Hands-on interactive exercise

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

# Print columns
print(df.____)

# Print data types of columns
print(df.____)

# Select and print numeric columns
numeric_df = df.____(include=['____', 'float'])
print(numeric_df.____)

# Select and print categorical columns 
categorical_df = df.____(include=['____'])
print(categorical_df.____)
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