I was trying out `numpy.linalg.eig`

and the output wasn’t as predicted

Ax = λx where

- A is a matrix
- λ is eigenvalue
- x is eigenvector

Here’s the code

```
import numpy as np
from numpy import linalg
A = np.array([[2,3],[-1,3]])
eigenvalues,eigenvectors = linalg.eig(A)
leftside = A[0]*eigenvectors[:,0]
rightside = eigenvalues[0]*eigenvectors[:,0]
print(leftside)
print(rightside)
```

I expected the leftside to be equal to the right side but the outputs are different?

```
[1.73205081+0.j 0.4330127 +1.43614066j]
[ 2.16506351+1.43614066j -0.4330127 +1.43614066j]
```

Why does this occur?

How do I make the equation work? ( as in the left side will be equal to the right side )

Source: Python Questions