Hi all!
I'd like to re-shape it to get the following data frame:
In the second data frame, the values are representative of the amount of money that flow through eCommerce (eCommerce purchase value / (eCommerce + Brick and Mortar purchase value) for each customer, for each month.
Between the groupby, aggregate, stack/unstack, and pivot functions, I'm lost as how to approach this problem. I am using python/pandas.
Thank you!
Python:
df = pd.DataFrame({'Customer': ['Sarah', 'Sarah', 'Sarah', 'Bob', 'Bob',
'Bob'],
'Channel': ['eCommerce', 'Brick and Mortar Store', 'eCommerce', 'eCommerce',
'Brick and Mortar Store', 'eCommerce'],
'Purchase Value': [90, 60, 30, 30, 50, 50],
'Month of Purchase': ['Jan', 'Jan', 'Feb', 'Jan', 'Feb', 'Feb']})
I'd like to re-shape it to get the following data frame:
Python:
df1 = pd.DataFrame({'Customer': ['Sarah', 'Bob'],
'Jan': [.6,1],
'Feb':[1,.5]})
In the second data frame, the values are representative of the amount of money that flow through eCommerce (eCommerce purchase value / (eCommerce + Brick and Mortar purchase value) for each customer, for each month.
Between the groupby, aggregate, stack/unstack, and pivot functions, I'm lost as how to approach this problem. I am using python/pandas.
Thank you!