Assign labels to raw data
You will now analyze the average RFM values of the three clusters you've created in the previous exercise. We have loaded the raw RFM dataset as datamart_rfm
, and the cluster labels as cluster_labels
. pandas
is available as pd
.
Feel free to explore the date in the console.
This exercise is part of the course
Customer Segmentation in Python
Exercise instructions
- Create a new DataFrame by adding a cluster label column to
datamart_rfm
. - Create a
groupby
element on aCluster
column. - Calculate average RFM values and segment sizes per each
Cluster
value.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a DataFrame by adding a new cluster label column
datamart_rfm_k3 = datamart_rfm.____(Cluster=cluster_labels)
# Group the data by cluster
grouped = ____.____(['____'])
# Calculate average RFM values and segment sizes per cluster value
grouped.____({
'Recency': '____',
'Frequency': '____',
'MonetaryValue': ['____', '____']
}).round(1)