1. Learn
    2. /
  2. Courses
    3. /
  3. Marketing Analytics: Predicting Customer Churn in Python

Exercise

Churn by State

When dealing with customer data, geographic regions may play an important part in determining whether a customer will cancel their service or not. You may have noticed that there is a 'State' column in the dataset. In this exercise, you'll group 'State' and 'Churn' to count the number of churners and non-churners by state. For example, if you wanted to group by x and aggregate by y, you could use .groupby() as follows:

df.groupby('x')['y'].value_counts()

Instructions 1/2

undefined XP
    1
    2

Group telco by 'State', aggregate by 'Churn', and then use value_counts() to count the number of churners and non-churners by state.