Experimental units: Revenue per user day
We are going to check what happens when we add a consumable paywall to our app. A paywall is a feature of a website or other technology that requires payment from users in order to access additional content or services.
Here, you'll practice calculating experimental units and baseline values related to our consumable paywall. Both measure revenue only among users who viewed a paywall. Your job is to calculate revenue per user-day, with user-day as the experimental unit.
The purchase_data dataset has been loaded for you.
This exercise is part of the course
Customer Analytics and A/B Testing in Python
Exercise instructions
- Extract the 'day' value from the
datetimestamp as you saw in the video: Using.date.dt.floor('d'). - To make the calculations easier, replace the
NaNpurchase_data.price values with 0 by using thenp.where()method. - Finally, find the mean amount paid per user-day among paywall viewers. To do this, you need to first aggregate the data by
'uid'and'date', which has been done for you.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Extract the 'day'; value from the timestamp
purchase_data.date = purchase_data.____
# Replace the NaN price values with 0
purchase_data.price = np.where(np.isnan(purchase_data.price), ____, purchase_data.price)
# Aggregate the data by 'uid' & 'date'
purchase_data_agg = purchase_data.groupby(by=['uid', 'date'], as_index=False)
revenue_user_day = purchase_data_agg.sum()
# Calculate the final average
revenue_user_day = revenue_user_day.price.____()
print(revenue_user_day)