Building a PairGrid
When exploring a dataset, one of the earliest tasks is exploring the relationship between pairs of variables. This step is normally a precursor to additional investigation.
Seaborn supports this pair-wise analysis using the PairGrid. In this exercise,
we will look at the Car Insurance Premium data we analyzed in Chapter 1. All data
is available in the df variable.
Questo esercizio fa parte del corso
Intermediate Data Visualization with Seaborn
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Create a PairGrid with a scatter plot for fatal_collisions and premiums
g = sns.___(df, ___=["fatal_collisions", "premiums"])
g2 = g.___(sns.scatterplot)
plt.show()
plt.clf()