Heatmaps & 2D Data Visualization

What is a Heatmap?

A heatmap uses color intensity to represent values in a 2D matrix. Perfect for correlation matrices, confusion matrices, and time-series grids.

Basic Heatmap with imshow()

import matplotlib.pyplot as plt
import numpy as np

data = np.random.randn(10, 10)

fig, ax = plt.subplots()
im = ax.imshow(data, cmap='viridis')  # colormap
ax.set_title('2D Data Heatmap')
plt.colorbar(im, ax=ax)  # add color scale

Heatmaps with Text Labels

Perfect for correlation matrices where you want to see exact values:

import seaborn as sns

# Correlation matrix
corr_matrix = df.corr()

fig, ax = plt.subplots(figsize=(8, 8))
sns.heatmap(corr_matrix, annot=True, fmt='.2f', cmap='coolwarm',
            cbar_kws={'label': 'Correlation'}, ax=ax)
ax.set_title('Feature Correlation Matrix')

Popular Colormaps (Color Schemes)

Tip: Always use colorblind-friendly colormaps. Avoid jet and rainbow!