Seaborn Plots with 2 Legends

Posted here because I will inevitably forget this painfully worked-out answer for having legends for two different types of plots in Seaborn…

import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# We will need to access some of these matplotlib classes directly
from matplotlib.lines import Line2D # For points and lines
from matplotlib.patches import Patch # For KDE and other plots
from matplotlib.legend import Legend
from matplotlib import cm

# Initialise random number generator
rng = np.random.default_rng(seed=42)

# Generate sample of 25 numbers
n = 25

clusters = []

for c in range(0,3):
    # Crude way to get different distributions
    # for each cluster
p = rng.integers(low=1, high=6, size=4)
df = pd.DataFrame({
'x': rng.normal(p[0], p[1], n),
'y': rng.normal(p[2], p[3], n),
'name': f"Cluster {c+1}"

# Flatten to a single data frame
clusters = pd.concat(clusters)

# Now do the same for data to feed into
# the second (scatter) plot...
n = 8
points = []

for c in range(0,2):

p = rng.integers(low=1, high=6, size=4)

df = pd.DataFrame({
'x': rng.normal(p[0], p[1], n),
'y': rng.normal(p[2], p[3], n),
'name': f"Group {c+1}"

points = pd.concat(points)

# And create the figure
f, ax = plt.subplots(figsize=(8,8))

# The KDE-plot generates a Legend 'as usual'
k = sns.kdeplot(
x='x', y='y',

# Notice that we access this legend via the
# axis to turn off the frame, set the title,
# and adjust the patch alpha level so that
# it closely matches the alpha of the KDE-plot
for lh in ax.get_legend().get_patches():

# You would probably want to sort your data
# frame or set the hue and style order in order
# to ensure consistency for your own application
# but this works for demonstration purposes
groups =
markers = ['o', 'v', 's', 'X', 'D', '<', '>']
colors = cm.get_cmap('Dark2').colors

# Generate the scatterplot: notice that Legend is
# off (otherwise this legend would overwrite the
# first one) and that we're setting the hue, style,
# markers, and palette using the 'name' parameter
# from the data frame and the number of groups in
# the data.
p = sns.scatterplot(

# Here's the 'magic' -- we use zip to link together
# the group name, the color, and the marker style. You
# *cannot* retreive the marker style from the scatterplot
# since that information is lost when rendered as a
# PathCollection (as far as I can tell). Anyway, this allows
# us to loop over each group in the second data frame and
# generate a 'fake' Line2D plot (with zero elements and no
# line-width in our case) that we can add to the legend. If
# you were overlaying a line plot or a second plot that uses
# patches you'd have to tweak this accordingly.
patches = []
for x in zip(groups, colors[:len(groups)], markers[:len(groups)]):
patches.append(Line2D([0],[0], linewidth=0.0, linestyle='',
color=x[1], markerfacecolor=x[1],
marker=x[2], label=x[0], alpha=1.0))

# And add these patches (with their group labels) to the new
# legend item and place it on the plot.
leg = Legend(ax, patches, labels=groups,
loc='upper left', frameon=False, title='Groups')

# Done;

A Seaborn plot showing 2 legends for different types of plots.

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