Separate numerical and categorical columns

In the last exercise, you have explored the dataset characteristics and are ready to do some data pre-processing. You will now separate categorical and numerical variables from the telco_raw DataFrame with a customized categorical vs. numerical unique value count threshold. The pandas module has been loaded for you as pd.

The raw telecom churn dataset telco_raw has been loaded for you as a pandas DataFrame. You can familiarize with the dataset by exploring it in the console.

Store customerID and Churn column names.
Assign to categorical the column names that have less than 5 unique values.
Remove target from the list.
Assign to numerical all column names that are not in the custid, target and categorical.

Exercise

Separate numerical and categorical columns

Instructions