.groupby() and .sum() together
If you looked at our transaction-level data in the last exercise, you may have noticed some new columns, like movie_genre and ticket_type. In this exercise, we'll focus on summarizing our data by ticket_type. Tickets can be priced for adults, seniors, or children, and the ticket_type column contains the ticket type purchased during each transaction.
Let's use .groupby() and .sum() to create a summary table to understand how many of our tickets are of each ticket type.
The pandas package and the sales dataset has already been loaded for you.
This exercise is part of the course
Python for Spreadsheet Users
Exercise instructions
- Use
.groupby()and.sum()to create a summary table of ticket sales byticket_type. - Print the result,
ticket_type_summary, to the console.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create summary by ticket type
ticket_type_summary = sales.____(____, as_index=False).____()
# Print ticket_type_summary