How can I visualize PCA results in Python?

How can I visualize PCA results in Python?

You can use libraries like Matplotlib and Seaborn to visualize PCA results. Would you like a code example?

Yes, please provide a code example for PCA visualization.

Sure! Here's a simple example:

import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from sklearn.datasets import load_iris

# Load dataset
iris = load_iris()
X = iris.data

# Apply PCA
pca = PCA(n_components=2)
X_pca = pca.fit_transform(X)

# Plotting
plt.figure(figsize=(8, 6))
plt.scatter(X_pca[:, 0], X_pca[:, 1], c=iris.target)
plt.xlabel('Principal Component 1')
plt.ylabel('Principal Component 2')
plt.title('PCA of Iris Dataset')
plt.colorbar()
plt.show()

What do the principal components represent in this visualization?

The principal components represent the directions of maximum variance in the data. They help in reducing dimensionality while preserving as much information as possible.