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.
Questo esercizio fa parte del corso
Customer Segmentation in Python
Istruzioni dell'esercizio
- 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.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# 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.____(____))