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.
Este ejercicio forma parte del curso
Customer Segmentation in Python
Instrucciones del ejercicio
- Create a spend quartile with 4 groups - a range between 1 and 5.
- Assign the quartile values to the
Spend_Quartilecolumn indata. - Sort
databased on theSpendvalues and print the result.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# 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(____))