Calculate RFM Score

Great work, you will now finish the job by assigning customers to three groups based on the MonetaryValue percentiles and then calculate an RFM_Score which is a sum of the R, F, and M values.

The datamart has been loaded with the R and F values you have created in the previous exercise.

Diese Übung ist Teil des Kurses

Customer Segmentation in Python

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Anleitung zur Übung

Create labels for MonetaryValue with an increasing range of 1 through 3.
Assign these labels to three equal percentile groups based on MonetaryValue.
Create new column M based on the MonetaryValue percentile group.
Calculate RFM_Score based on the sum of R, F, and M column values.

Interaktive Übung

Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.

# Create labels for MonetaryValue
m_labels = range(1, ____)

# Assign these labels to three equal percentile groups 
m_groups = pd.qcut(datamart['MonetaryValue'], q=____, labels=____)

# Create new column M
datamart = datamart.assign(____=____)

# Calculate RFM_Score
datamart['RFM_Score'] = datamart[['R','F','M']].____(axis=____)
print(datamart['____'].head())

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