Seaborn vs Matplotlib: Which is Better for Heatmaps?

What are the main differences between Seaborn and Matplotlib when creating heatmaps?

Seaborn is built on top of Matplotlib and provides a higher-level interface for creating attractive heatmaps with less code. Matplotlib offers more customization options but requires more lines of code to achieve similar results.

Can you show me an example of a heatmap created with both libraries?

Sure! Here's a simple example:

Matplotlib:

import matplotlib.pyplot as plt
import numpy as np

data = np.random.rand(10, 12)
plt.imshow(data, cmap='hot', interpolation='nearest')
plt.colorbar()
plt.show()

Seaborn:

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

data = np.random.rand(10, 12)
sns.heatmap(data, cmap='hot')
plt.show()

Which one should I use for a publication-quality figure?

Seaborn is often preferred for publication-quality figures due to its aesthetic defaults and ease of use. However, if you need detailed customization, Matplotlib might be the better choice.

Are there any performance differences between the two?

In general, performance differences are minimal for small datasets. However, for larger datasets, Matplotlib may be slightly faster due to its lower-level operations. Seaborn's additional features can introduce some overhead.