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

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Exercise instructions

Create a spend quartile with 4 groups - a range between 1 and 5.
Assign the quartile values to the Spend_Quartile column in data.
Sort data based on the Spend 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(____))

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