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  3. Introduction to Data Visualization with Seaborn

Exercise

Creating two-factor subplots

Let's continue looking at the student_data dataset of students in secondary school. Here, we want to answer the following question: does a student's first semester grade ("G1") tend to correlate with their final grade ("G3")?

There are many aspects of a student's life that could result in a higher or lower final grade in the class. For example, some students receive extra educational support from their school ("schoolsup") or from their family ("famsup"), which could result in higher grades. Let's try to control for these two factors by creating subplots based on whether the student received extra educational support from their school or family.

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

Instructions 1/3

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  • Use relplot() to create a scatter plot with "G1" on the x-axis and "G3" on the y-axis, using the student_data DataFrame.