Engineering a new column
Leveraging domain knowledge to engineer new features is an essential part of modeling. This quote from Andrew Ng summarizes the importance of feature engineering:
Coming up with features is difficult, time-consuming, requires expert knowledge. "Applied machine learning" is basically feature engineering.
Your job in this exercise is to create a new feature that contains information about the average length of night calls made by customers.
This exercise is part of the course
Marketing Analytics: Predicting Customer Churn in Python
Exercise instructions
- Create a new feature -
'Avg_Night_Calls'
- that is the result of dividing'Night_Mins
by'Night_Calls'
. - Print the first five rows of this new feature.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create the new feature
telco['____'] = ____
# Print the first five rows of 'Avg_Night_Calls'
print(____)