Mastering Python for Data Science

Heatmaps

A heatmap is a graphical representation where individual values of a matrix are represented as colors. A heatmap is very useful in visualizing the concentration of values between two dimensions of a matrix. This helps in finding patterns and gives a perspective of depth.

Let's start off by creating a basic heatmap between two dimensions. We'll create a 10 x 6 matrix of random values and visualize it as a heatmap:

>>> # Generate Data
>>> data = np.random.rand(10,6)
>>> rows = list('ZYXWVUTSRQ')  #Ylabel
>>> columns = list('ABCDEF')  #Xlabel

>>> #Basic Heat Map plot
>>> plt.pcolor(data)
>>> plt.show()

After the preceding code is executed we'll get the following output:

In the preceding code, we used the pcolor() function to create the heatmap ...