How can I create advanced heatmaps using Matplotlib?

How can I create advanced heatmaps using Matplotlib?

You can create advanced heatmaps in Matplotlib by customizing color maps, adding annotations, and adjusting the grid size. Would you like to see an example?

Yes, please show me an example with annotations.

Sure! Here's a simple example:

import numpy as np
import matplotlib.pyplot as plt

# Create data
data = np.random.rand(10, 10)

# Create heatmap
plt.imshow(data, cmap='hot', interpolation='nearest')

# Add annotations
for (i, j), val in np.ndenumerate(data):
    plt.text(j, i, f'{val:.2f}', ha='center', va='center', color='white')

plt.colorbar()
plt.show()

This code generates a heatmap with random data and adds annotations to each cell.

How can I customize the color map further?

You can customize the color map by using predefined colormaps or creating your own. For example, you can use cmap='viridis' or define a custom colormap using matplotlib.colors.LinearSegmentedColormap. Would you like to see how to create a custom colormap?