Regression and residual plots
Linear regression is a useful tool for understanding the relationship between numerical variables. Seaborn has simple but powerful tools for examining these relationships.
For these exercises, we will look at some details from the US Department of Education on 4 year college tuition information and see if there are any interesting insights into which variables might help predict tuition costs.
For these exercises, all data is loaded in the df variable.
Questo esercizio fa parte del corso
Intermediate Data Visualization with Seaborn
esercizio interattivo pratico
Prova questo esercizio completando questo codice di esempio.
# Display a regression plot for Tuition
sns.____(data=df,
y='____',
x='SAT_AVG_ALL',
marker='^',
color='g')
plt.show()
plt.clf()