What is the best way to plot a two-dimensional (bivariate) probability distribution (scipy.stats.norm
) in 3d like the example surface plots below. I don't think seaborn
comes out of the box with these, but thinking first in terms of pyplot
or pylab
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1Some similar questions are [3D Probability Density Plots in Python](https://stackoverflow.com/questions/52247430/3d-probability-density-plots-in-python), [Plot normal distribution in 3D](https://stackoverflow.com/questions/38698277/plot-normal-distribution-in-3d) and [How to plot 3d gaussian distribution?](https://stackoverflow.com/questions/40622203/how-to-plot-3d-gaussian-distribution-with-matplotlib) – JohanC Jan 16 '21 at 22:43
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3FYI: ["Since heavily importing into the global namespace may result in unexpected behavior, the use of pylab is strongly discouraged. Use matplotlib.pyplot instead."](https://matplotlib.org/api/index.html?highlight=pylab#module-pylab) – Mr. T Jan 17 '21 at 00:13
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Without the projections of the surface's profiles on to the side panels, I would consider this post `duplicate`. ;P – swatchai Jan 17 '21 at 04:04