How do I compute eigenvalues using NumPy?

How do I compute eigenvalues using NumPy?

You can compute eigenvalues in NumPy using the numpy.linalg.eig function. Just pass your matrix to it.

Can you show me an example with a 2x2 matrix?

Sure! Here's a simple example:

import numpy as np

A = np.array([[4, 2], [1, 3]])
eigenvalues, eigenvectors = np.linalg.eig(A)
print('Eigenvalues:', eigenvalues)

What if my matrix is not square?

Eigenvalues are only defined for square matrices. You would need to reshape or modify your matrix to be square.

How can I visualize the eigenvectors?

You can use Matplotlib to visualize eigenvectors. Plot them as arrows originating from the origin.