pair of attributes.

import seaborn
from matplotlib import pyplot

df = seaborn.load_dataset("iris")
seaborn.pairplot(data=df, kind="kde")
pyplot.savefig("seaborn-pairplot-kde.png")
pyplot.close()

The resulting pairplot will look like the following:

And if we use reg as the underlying plotting function, then we will get the data and a linear regression model fit for every pair of variables or attributes.

import seaborn
from matplotlib import pyplot

df = seaborn.load_dataset("iris")
seaborn.pairplot(data=df, kind="reg")
pyplot.savefig("seaborn-pairplot-reg.png")
pyplot.close()

The resulting pairplot will look like the following: