How to Compute Eigenvalues and Eigenvectors in Python Using SymPy (in 75 seconds)
Learn how to calculate eigenvalues and eigenvectors of a matrix in Python using the SymPy library! This tutorial walks you through defining matrices, finding eigenvalues, and extracting eigenvectors, including their multiplicities. Perfect for linear algebra students, Python learners, and anyone interested in matrix transformations and numerical methods.
✅ What You’ll Learn:
Defining a 2x2 matrix using the Matrix class in SymPy.
Calculating eigenvalues of a matrix using eigenvals().
Extracting eigenvectors and their multiplicities using eigenvects().
Practical examples to strengthen your understanding of eigenvalue problems.
🎯 Why Watch This Video?
Eigenvalues and eigenvectors are essential concepts in linear algebra, with applications in machine learning, physics, and data analysis. This tutorial simplifies these concepts and shows how to compute them in Python step by step.
📊 Who Is This For?
Perfect for Python beginners, students studying linear algebra, and anyone looking to apply Python to solve matrix-related problems.
🔗 Code From the Tutorial:
***
from sympy import Matrix
Define a 2x2 matrix
A = Matrix([
[1, 1],
[4, 1],
])
Compute the Eigenvalues
A.eigenvals()
Compute the Eigenvectors
eig = A.eigenvects()
for i in eig:
print(f'Eigenvalue: {i[0]}')
print(f'Eigenvector: {i[2]}')
print('Multiplicity: ', i[1])
print()
***
🔗 Related Topics Covered:
Linear Algebra in Python
Eigenvalues and Eigenvectors Explained
SymPy for Numerical Computations