How to Create 3D Plot in Python Matplotlib

In this Matplotlib article we are going to learn How to Create 3D Plot in Python Matplotlib, so data visualization becomes even more powerful when we can explore the data in three dimensions. Python Matplotlib library provides easy capabilities for creating 3D plots, and you can use that to visualize complex relationships and patterns in our data. 



For plotting 3D plots, first we need to install Matplotlib library.



For creating a 3D plot, we start by creating a figure and axes using plt.subplots() function. we pass the subplot_kw parameter with the keyword argument projection=3d to specify that we want a 3D plot.



For demonstrating the 3D plot, we can generate some dummy data. we want to create three arrays x, y, and z, these arrays represent the coordinates in the 3D space.



We can use the plot_surface() function, we can create a 3D plot surface based on the generated data.



Matplotlib provides different customization options for 3D plots. You can add labels, change colors, adjust viewing angles and many more.



For showing the 3D plot, we can use the function.



Also If you want to save the 3D plot as an image, you can use plt.savefig() function instead.




This is the complete code for this article




Run the complete code and this will be the output

How to Create 3D Plot in Python Matplotlib
How to Create 3D Plot in Python Matplotlib




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