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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 dataset 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.