How to animate a Seaborn heatmap or correlation matrix(Matplotlib)?

To animate a Seaborn heatmap or correlation matrix, we can take the following steps −

• Set the figure size and adjust the padding between and around the subplots.
• Create a new figure or activate an existing figure.
• Make a dimension tuple.
• Make a Seaborn heatmap.
• Create an init() method for the first heatmap.
• Use FuncAnimation() class to make an animation by repeatedly calling a function animate that will create a random dataset and create a heatmap.
• To display the figure, use show() method.

Example

import numpy as np import seaborn as sns import matplotlib.pyplot as plt from matplotlib import animation plt.rcParams["figure.figsize"] = [7.50, 3.50] plt.rcParams["figure.autolayout"] = True fig = plt.figure() dimension = (5, 5) data = np.random.rand(dimension[0], dimension[1]) sns.heatmap(data, vmax=.8) def init():     sns.heatmap(np.zeros(dimension), vmax=.8, cbar=False) def animate(i):     data = np.random.rand(dimension[0], dimension[1])     sns.heatmap(data, vmax=.8, cbar=False) anim = animation.FuncAnimation(fig, animate, init_func=init, frames=20, repeat=False) plt.show()

Output