Calculate average price
You will now calculate the average price metric and analyze if there are any differences in shopping patterns across time and across cohorts.
The online dataset has been loaded to you with monthly cohorts and cohort index assigned from this lesson. Feel free to print it to the Console.
This exercise is part of the course
Customer Segmentation in Python
Exercise instructions
- Create a
groupbyobject and pass the monthly cohort and cohort index as a list. - Select the unit price column, calculate the average, and store it to
cohort_data. - Reset the index of
cohort_dataDataFrame. - Create a pivot with monthly cohort in the index, cohort index in the columns and the unit price in the values, and print the result.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a groupby object and pass the monthly cohort and cohort index as a list
grouping = online.groupby([____, ____])
# Calculate the average of the unit price column
cohort_data = grouping[____].____()
# Reset the index of cohort_data
cohort_data = cohort_data.____()
# Create a pivot
average_price = cohort_data.____(index=____, columns=____, values=____)
print(average_price.round(1))