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Exercise

Practicing aggregations

It's time to begin exploring the in-app purchase data in more detail. Here, you will practice aggregating the dataset in various ways using the .agg() method and then examine the results to get an understanding of the overall data, as well as a feel for how to aggregate data using pandas.

Loaded for you is a DataFrame named purchase_data which is the dataset of in-app purchase data merged with the user demographics data from earlier.

Before getting started, it's good practice to explore this purchase_data DataFrame in the IPython Shell. In particular, notice the price column: you'll examine it further in this exercise.

Instructions 1/3
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  • 1

    Find the 'mean' purchase price paid across our dataset. Then examine the output before moving on.

    • 2

      Now, use the .agg() method to find the 'mean' and 'median' prices together.

    • 3

      Now, find the 'mean' and 'median' for both the 'price' paid and the 'age' of purchaser.