Add parameter `col_wrap` to `pairplot`

[albertotb]

Currently, a very convenient way to plot an scatter plot of all the columns against one in a pd.DataFrame is

import seaborn as sns

iris = sns.load_dataset('iris')
sns.pairplot(iris, 
             x_vars=['sepal_length', 'sepal_width', 'petal_length'] , 
             y_vars=['petal_width'])

However, all the plots are in a single row, which is a problem if there are many x_vars . A possible solution is to add a col_wrap parameter that wraps the plot matrix.

I know that for this case the name of the function pairplot does not make much sense, but since the parameters x_vars and y_vars make it flexible enough to do this kind of plots I think it would be a good addition.

[mwaskom]

This is a good idea.

In the meantime, here's a clever workaround:

iris = sns.load_dataset('iris')
x_vars = ['sepal_length', 'sepal_width', 'petal_length']
y_var = "petal_width"

g = sns.FacetGrid(pd.DataFrame(x_vars), col=0, col_wrap=2, sharex=False)
for ax, x_var in zip(g.axes, x_vars):
    sns.scatterplot(data=iris, x=x_var, y=y_var, ax=ax)
g.tight_layout()

[mwaskom]

In the new objects interface the Plot.pair operator has wrapping (across rows or columns):

(
    so.Plot(mpg, y="mpg")
    .pair(x=["displacement", "weight", "horsepower", "cylinders"], wrap=2)
    .add(so.Dots())
)

I'm going to close this issue, as supporting wrapping in PairGrid itself will be tricker. Not ruling it out, but also not planning to do it in any particular interval.