Calculate spend quartiles (q=4)
We have created a dataset for you with random CustomerID
and Spend
values as data
. You will now use this dataset to group customers into quartiles based on Spend
values and assign labels to each of them.
pandas
library as been loaded as pd
. Feel free to print the data
to the console.
This exercise is part of the course
Customer Segmentation in Python
Exercise instructions
- Create a spend quartile with 4 groups - a range between 1 and 5.
- Assign the quartile values to the
Spend_Quartile
column indata
. - Sort
data
based on theSpend
values and print the result.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a spend quartile with 4 groups - a range between 1 and 5
spend_quartile = pd.____(data['Spend'], q=____, labels=range(1,____))
# Assign the quartile values to the Spend_Quartile column in data
data['____'] = spend_quartile
# Print data with sorted Spend values
print(____.sort_values(____))