Exercise

.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 data set has already been loaded for you.

Instructions

100 XP

Use .groupby() and .sum() to create a summary table of ticket sales by ticket_type.
Print the result, ticket_type_summary, to the console.