The idea is straightforward, replace numbers with colors.
Now, this visualization style came a long way from simple color-coded tables, it became widely used with geospatial data, and its commonly applied for describing density or intensity of variables, visualize patterns, variance, and even anomalies.
With so many applications, this elementary method deserves some attention. In this article, we’ll go through the basics of heatmaps, and see how to create them using Matplotlib, and Seaborn.
