The **mplot3D** toolkit of Matplotlib allows to easily create 3D scatterplots. Note that most of the customisations presented in the Scatterplot section will work in 3D as well. The result can be a bit disappointing since each marker is represented as a dot, not as a sphere..

# libraries from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np import pandas as pd # Dataset df=pd.DataFrame({'X': range(1,101), 'Y': np.random.randn(100)*15+range(1,101), 'Z': (np.random.randn(100)*15+range(1,101))*2 }) # plot fig = plt.figure() ax = fig.add_subplot(111, projection='3d') ax.scatter(df['X'], df['Y'], df['Z'], c='skyblue', s=60) ax.view_init(30, 185) plt.show()

Typo in the last line, it should be:

plt.show()

Thx Iñigo, just corrected it!

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How can one add labels to this plot?

plt.xlabel(‘Glucose Levels’)

plt.ylabel(‘Tricep Thickness(mm)’)

ax.set_zlabel(‘BMI Levels’)