In order to do this, we can use the c= parameter. This allows us to better understand the third dimension. Three dimensions can be quite difficult to visualize and adding color to this can be quite helpful. It can be quite helpful to add color to a 3-dimensional plot. Finally, we showed the plot using plt.show()Ĭhanging Color of Points in 3D Scaterplots in Matplotlib.We plotted a scatter3D plot on our axes, passing in the three arrays of data.We imported our libraries and created some variables containing data.
Our axes will specify that we’ll want to project the data onto three dimensions, by passing in projection='3d'.įrom there, we can easily create a 3D scatterplot using the ax.scatter3D() function: # Creating out first 3D scatterplot in Matplotlib We’ll first set up our figure, fig, and axes, ax, to hold our visualization. Let’s begin by importing our libraries and setting up some variables to plot. This allows us to easily project data onto a third dimension. In order to create 3D scatterplots in Matplotlib we can import some additional helper modules from Matplotlib.
Creating a 3D Scatterplot in Matplotlib.
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