Binning data
When the data on the x axis is a continuous value, it can be useful to break it into different bins in order to get a better visualization of the changes in the data.
For this exercise, we will look at the relationship between tuition and the
Undergraduate population abbreviated as UG in this data. We will start by looking at a
scatter plot of the data and examining the impact of different bin sizes on the
visualization.
This exercise is part of the course
Intermediate Data Visualization with Seaborn
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create a scatter plot by disabling the regression line
sns.regplot(data=df,
y='Tuition',
x='UG',
fit_reg=____)
plt.show()
plt.clf()