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  3. Introduction to Data Visualization with Seaborn

Exercise

Customizing bar plots

In this exercise, we'll explore data from students in secondary school. The "study_time" variable records each student's reported weekly study time as one of the following categories: "<2 hours", "2 to 5 hours", "5 to 10 hours", or ">10 hours". Do students who report higher amounts of studying tend to get better final grades? Let's compare the average final grade among students in each category using a bar plot.

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 bar plot with "study_time" on the x-axis and final grade ("G3") on the y-axis, using the student_data DataFrame.