A missed phone call
You finished reshaping your churn
dataset in the previous exercises. Now, it is ready to be used. You remember that something caught your attention. You are sure you saw a clear pattern in the data.
Before you fit a classification model, you decide to do something simpler. You want to see what else you can learn from the data. You will reshape your data by unstacking levels, but you know this process will generate missing data that you need to handle.
The churn
DataFrame contains different features of customers located in Los Angeles and New York, and is available for you. Make sure to examine it in the console!
This exercise is part of the course
Reshaping Data with pandas
Exercise instructions
- Reshape the
churn
DataFrame by unstacking the level namedchurn
, filling the missing values with zero. - Sort the
churn
DataFrame by thevoice_mail_plan
column in descending order, then byinternational_plan
column in ascending order. - Print the final
churn_sorted
DataFrame.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Unstack churn level and fill missing values with zero
churn = ____.____(level=____, ____=____)
# Sort by descending voice mail plan and ascending international plan
churn_sorted = churn.____(____=[____, ____],
____=[____, ____])
# Print final DataFrame and observe pattern
print(____)