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  3. Introduction to Data Visualization with Seaborn

Exercise

Count plots

In this exercise, we'll return to exploring our dataset that contains the responses to a survey sent out to young people. We might suspect that young people spend a lot of time on the internet, but how much do they report using the internet each day? Let's use a count plot to break down the number of survey responses in each category and then explore whether it changes based on age.

As a reminder, to create a count plot, we'll use the catplot() function and specify the name of the categorical variable to count (x=____), the pandas DataFrame to use (data=____), and the type of plot (kind="count").

Seaborn has been imported as sns and matplotlib.pyplot has been imported as plt.

Instructions 1/3

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  • Use sns.catplot() to create a count plot using the survey_data DataFrame with "Internet usage" on the x-axis.