Exercise

# Create and interpret a box plot

Let's continue using the `student_data`

dataset. In an earlier exercise, we explored the relationship between studying and final grade by using a bar plot to compare the average final grade (`"G3"`

) among students in different categories of `"study_time"`

.

In this exercise, we'll try using a box plot look at this relationship instead. As a reminder, to create a box plot you'll need to use the `catplot()`

function and specify the name of the categorical variable to put on the x-axis (`x=____`

), the name of the quantitative variable to summarize on the y-axis (`y=____`

), the Pandas DataFrame to use (`data=____`

), and the type of plot (`kind="box"`

).

We have already imported `matplotlib.pyplot`

as `plt`

and `seaborn`

as `sns`

.

Instructions 1/2

**undefined XP**

- Use
`sns.catplot()`

and the`student_data`

DataFrame to create a box plot with`"study_time"`

on the x-axis and`"G3"`

on the y-axis. Set the ordering of the categories to`study_time_order`

.