Finding the eigenvalues of a matrix

Overview:

Given a matrix the function eigvals() returns the eigen values of the matrix.
When a matrix is multiplied by a vector if the result is scalar times of that vector, the vector is known as eigenvector. The scalar value is known as eigenvalue.
The eigenvectors and eigenvalues exist only for square matrices.

# Example Python program that finds the eigenvalues of a matrix
import numpy

# Control the printing format of floating point numbers
numpy.set_printoptions(suppress=True, formatter={'float_kind':'{:0.2f}'.format})

# Create a matrix
numbers = numpy.arange(-25, 20, 5)
matrix = numbers.reshape(3, 3)
print("The matrix:")
print(matrix)

# Find the eigen values of the matrix
evs = numpy.linalg.eigvals(matrix)
print("Eigen values of the matrix:")
print(evs)

The matrix:

[[-25 -20 -15]

[-10 -5 0]

[ 5 10 15]]

Eigen values of the matrix:

[-30.00 0.00 15.00]