Calculate relative importance of each attribute
Now you will calculate the relative importance of the RFM values within each cluster.
We have loaded datamart_rfm with raw RFM values, and datamart_rfm_k3 which has raw RFM values and the cluster labels stored as Cluster. The pandas library is also loaded as pd.
Feel free to explore the datasets in the console.
Este ejercicio forma parte del curso
Customer Segmentation in Python
Instrucciones del ejercicio
- Calculate average RFM values for each cluster - use
datamart_rfm_k3dataset. - Calculate average RFM values for the total customer population - use
datamart_rfmdataset. - Calculate relative importance of cluster's attribute value compared to population.
- Print relative importance scores rounded to 2 decimals.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
# Calculate average RFM values for each cluster
cluster_avg = ____.groupby(['____']).____()
# Calculate average RFM values for the total customer population
population_avg = ____.____()
# Calculate relative importance of cluster's attribute value compared to population
relative_imp = ____ / ____ - ____
# Print relative importance scores rounded to 2 decimals
print(relative_imp.____(____))