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Course Notes

Use this workspace to take notes, store code snippets, or build your own interactive cheatsheet! The datasets used in this course are available in the datasets folder.

# Import any packages you want to use here
import pandas as pd
import numpy as np

Take Notes

Add notes here about the concepts you've learned and code cells with code you want to keep.

Add your notes here

# Calculate Recency, Frequency and Monetary value for each customer 
datamart = online.groupby(['CustomerID']).agg({
    'InvoiceDate': lambda x: (snapshot_date - x.max()).days,
    'InvoiceNo': 'count',
    'TotalSum': 'sum'})

# Rename the columns 
datamart.rename(columns={'InvoiceDate': 'Recency',
                         'InvoiceNo': 'Frequency',
                         'TotalSum': 'MonetaryValue'}, inplace=True)

# Print top 5 rows
print(datamart.head())