Python – 3D scatterplots in Python with hue colormap and legend

matplotlibpythonseaborn

I have been searching for 3D plots in python with seaborn and haven't seen any. I would like to 3D plot a dataset that I originally plotted using seaborn pairplot. Can anyone help me with these 2 issues:

I am not able to get same color palette as sns pairplot, e.g. how to get the color palette from figure 2 and apply to the points on figure 1?
The legend does not stick to the plot or does not show up as nice on pairplot, e.g. When I do plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.,ncol=4) I see the following error: anaconda2/lib/python2.7/site-packages/matplotlib/axes/_axes.py:545: UserWarning: No labelled objects found. Use label='…' kwarg on individual plots. warnings.warn("No labelled objects found. "

Thanks in advance !
My references: How to make a 3D scatter plot in Python?
https://pythonspot.com/3d-scatterplot/
https://jakevdp.github.io/PythonDataScienceHandbook/04.12-three-dimensional-plotting.html

Here's a MWE:

import re, seaborn as sns, numpy as np, pandas as pd, random
from pylab import *
from matplotlib.pyplot import plot, show, draw, figure, cm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
sns.set_style("whitegrid", {'axes.grid' : False})

fig = plt.figure(figsize=(6,6))

ax = Axes3D(fig) # Method 1
# ax = fig.add_subplot(111, projection='3d') # Method 2

x = np.random.uniform(1,20,size=20)
y = np.random.uniform(1,100,size=20)
z = np.random.uniform(1,100,size=20)


ax.scatter(x, y, z, c=x, marker='o')
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()

#Seaborn pair plot
df_3d = pd.DataFrame()
df_3d['x'] = x
df_3d['y'] = y
df_3d['z'] = z

sns.pairplot(df_3d, hue='x')

Best Answer

The color palette from Seaborn can be turned into a Matplotlib color map from an instance of a ListedColorMap class initialized with the list of colors in the Seaborn palette with the as_hex() method (as proposed in this original answer).
From the Matplotlib documentation, you can generate a legend from a scatter plot with getting the handles and labels of the output of the scatter function.

The result of the code is shown in the picture below. Note that I generated more data points in order to better see that the colormap is the same. Also, the output of ListedColorMap outputs a color map with transparency variations, so I had to manually set alpha to 1 in the scatter plot.

import re, seaborn as sns
import numpy as np

from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.colors import ListedColormap

# generate data
n = 200
x = np.random.uniform(1, 20, size=n)
y = np.random.uniform(1, 100, size=n)
z = np.random.uniform(1, 100, size=n)

# axes instance
fig = plt.figure(figsize=(6,6))
ax = Axes3D(fig, auto_add_to_figure=False)
fig.add_axes(ax)

# get colormap from seaborn
cmap = ListedColormap(sns.color_palette("husl", 256).as_hex())

# plot
sc = ax.scatter(x, y, z, s=40, c=x, marker='o', cmap=cmap, alpha=1)
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

# legend
plt.legend(*sc.legend_elements(), bbox_to_anchor=(1.05, 1), loc=2)

# save
plt.savefig("scatter_hue", bbox_inches='tight')

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