Using Color Bars to Improve Data Readability

In this lesson, we will learn how to use a color bar to improve the readability of our data.

We'll cover the following

What is the colorbar?

While legend helps us identify the different elements of a chart, the feature only works for discrete data. If the data is continuous, how could we display it on the legend? colorbar can help us. The colorbar maps the values of an interval to the colors of a range. The user can then distinguish the approximate range of the data by color. colorbar is a very useful and beautiful feature.

The simplest way to draw a color bar is by calling colorbar().

Notice: In this lesson, the colorbar() is called from the figure object. Let’s see some of the parameters required by colorbar.

  • mappable: The matplotlib.cm.ScalarMappable described by the colorbar.
  • cax: The axes object onto which the color bar will be drawn.

What is matplotlib.cm.ScalarMappable?

In short, ScalarMappable is a class to map scaler data to RGBA. This class requires two parameters:

  • norm: A normalize class, which typically maps a range number to the interval [0, 1].
  • cmap: The colormap is used to map normalized data values to RGBA colors. Matplotlib has already defined many color maps, which we can use by calling plt.get_cmap() with a name as the parameter.