3D scatterplots in Python Matplotlib with hue colormap and legend

To plot 3D scatter plots in Python with hue colormap and legend, we can take the following steps−

• Set the figure size and adjust the padding between and around the subplots
• Create x, y and z data points using numpy.
• Create a new figure or activate an existing figure using figure() method.
• Get the current axes, creating one if necessary.
• Get the hue colormap, defining a palette.
• Plot x, y and z data points using scatter() method.
• Place a legend on the plot.
• To display the figure, use show() method.

Example

import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

x = np.random.rand(100)
y = np.random.rand(100)
z = np.random.rand(100)

fig = plt.figure()
ax = fig.gca(projection='3d')
cmap = ListedColormap(sns.color_palette("husl", 256).as_hex())
sc = ax.scatter(x, y, z, s=40, c=x, marker='o', cmap=cmap, alpha=1)
plt.legend(*sc.legend_elements(), bbox_to_anchor=(1.05, 1), loc=2)

plt.show()

Output