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.
Deze oefening maakt deel uit van de cursus
Customer Segmentation in Python
Oefeninstructies
- 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.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# 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(____))