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Plot scatter points on a 3D projection with varying marker size in Matplotlib
To plot scatter points on a 3D projection with varying marker size, we can take the following steps
- Set the figure size and adjust the padding between and around the subplots.
- Create xs, ys and zs data points using numpy
- Initialize a variable 's' for varying size of marker.
- Create a figure or activate an existing figure using figure() method.
- Add an axes to the current figure as a subplot arrangement using subplots() method.
- Plot the xs, ys, and zs data points using scatter() method.
- To display the figure, use show() method.
Example
import numpy as np from matplotlib import pyplot as plt plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True xs = np.random.randint(low=8, high=30, size=35) ys = np.random.randint(130, 195, 35) zs = np.random.randint(30, 160, 35) s = zs / ((ys * 0.01) ** 2) fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter(ys, zs, xs, s=s * 5, c=xs, cmap='copper') plt.show()
Output
Updated on: 01-Jun-2021
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