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
There is no color palette specification for fig 2 but it looks like it is the Paired qualitative colormap from matplotlib (from here). So you need to specify that in your code for the 3D plot with the cmap
argument and with the palette
option in your pairplot.
The legend is harder. You can make one from legend_elements. Better explained here.
So your code would look like this (I got rid of the unused imports):
import seaborn as sns, numpy as np, pandas as pd, random
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)
x = np.random.uniform(1,20,size=20)
y = np.random.uniform(1,100,size=20)
z = np.random.uniform(1,100,size=20)
g = ax.scatter(x, y, z, c=x, marker='o', depthshade=False, cmap='Paired')
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
# produce a legend with the unique colors from the scatter
legend = ax.legend(*g.legend_elements(), loc="lower center", title="X Values", borderaxespad=-10, ncol=4)
ax.add_artist(legend)
plt.show()
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)
# 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')