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.

Este exercício faz parte do curso

Customer Segmentation in Python

Ver curso

Instruções do exercício

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.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# 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())

Editar e executar o código