Let’s see what happens when we use our x array as our colors and use the 'Blues' colormap. You can find the various color maps that Matplotlib offers here. This allows us to create a gradient to show how the data moves forward. With sequential data, as we have in our example, we can pass in color maps. This allows us to either pass in a single color, in case we wanted to do keep the same color for all points, or an array of numbers to color based on value. ![]() For this, we can use the following attributes: plt.title () to set the title plt.setxlabel () to set the x-axis label plt. In order to do this, we can use the c= parameter. Adding Titles and Axis Labels to 3D Scatterplots in Matplotlib Because the 3D scatterplots use Matplotlib under the hood, we can easily apply axis labels and titles to our charts. ![]() This article will see how to use the matplotlib. This allows us to better understand the third dimension. The scatter plot is widely used by data analytics to find out the relationship between two numerical datasets. 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.
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