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.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.

Cet exercice fait partie du cours

Python for Spreadsheet Users

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Instructions

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

Exercice interactif pratique

Essayez cet exercice en complétant cet exemple de code.

# Create summary by ticket type
ticket_type_summary = sales.____(____, as_index=False).____()

# Print ticket_type_summary
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