Seaborn pairplot legend - how to control position

To control the position of the default pairplot legend:

    g._legend.set_bbox_to_anchor((0.5, 0.5))

This is actually a lot easier than you'd think it is. It's simply a default setting in the actual matplot output. Just go to the configure subplot button at the top of your output window, and lower your right border upper limit a little and it'll be fixed.

pairplot already adds a legend outside the plot matrix and it is not clear where you want to move it. The other legends are probably being positioned as you requested even if that might be not what you actually want.

plt.legend will attach a legend to the current axes and there can be only one legend per axes so in your code only the last legend is drawn. But you can attach several legends to a figure and IIUC you want to position the legends relative to the figure so figure legends seems like the best option.

In order to plot figure legends you need to explicitly pass the handlers and labels. I had to use the private attribute PairPlot._legend_data for that, I did not find a way to do it using the public API.

Unfortunately matplotlib won't automatically make room to acomodate these legends and they will overlap with the subplots unless you make some adjustments. I will just use subplot_adjust with some hardcoded values that work for me in this case because calculations are tricky.

So this is the code that hopefully does what you want:

g = sns.pairplot(iris, hue='species', palette='husl', markers='d', size=2.5, plot_kws=
    {
    "s":40,
    "alpha":1.0,
    'lw':0.5,
    'edgecolor':'k'
    })

handles = g._legend_data.values()
labels = g._legend_data.keys()
g.fig.legend(handles=handles, labels=labels, loc='upper center', ncol=1)
g.fig.legend(handles=handles, labels=labels, loc='lower center', ncol=3)
g.fig.legend(handles=handles, labels=labels, loc='upper left', ncol=3)
g.fig.subplots_adjust(top=0.92, bottom=0.08)

The OP asked in a comment whether this can be found in the seaborn documentation. Of course part of this is just pure matplotlib, not specific to seaborn. But I also realized that I had to rely on a couple of undocumented features.

The fact that PairGrid has a fig attribute referencing the Figure instance is not documented. Anyway that was an easy guess and I could have used fig = plt.gcf() instead.

Getting the labels and handles of the legend is trickier. I learnt about the _legend_data attribute by looking at the docstring of PairGrid.add_legend, but the docstring itself is a bit hidden (it does not appear in the web) and the attribute is underscored as if it were private, so using it feels uncomfortable. I find it inconsistent that a private attribute is mentioned in the docstring of a public method, probably we should have legend_data as a public attribute, but I digress.

Alternatively you could try to extract the labels and handles from the subplots. You could guess that the subplots have this information but there are no actual guaranties so this means relying on undocumented behaviour. It turns out that the non-diagonal subplots have it (but the diagonal ones don't, so if you just looked at the first subplot you would be misguided) and you can do handles, labels = fig.get_axes()[1].get_legend_handles_labels(). But as I said this is undocumented behaviour even if you are using only documented API.

You could also create your own handles but it would be cumbersome, that's why I looked for shortcuts, even if undocumented.