### 2.46.2 Eigenvalues : `egvl eigenvalues eigVl`

`egvl` (or `eigenvalues eigVl`) takes as argument a square matrix A of size n.
`egvl` (or `eigenvalues eigVl`) returns the Jordan normal form of A.
Remark : If A is exact, `Xcas` may not be able to find the exact roots of the characteristic polynomial, `eigenvalues` will return an approximate diagonalozation of A if the coefficients are numeric.
Input :

`egvl([[4,1,-2],[1,2,-1],[2,1,0]])`

Output :

`[[2,1,0],[0,2,1],[0,0,2]]`

Input :

`egvl([[4,1,0],[1,2,-1],[2,1,0]])`

Output :

`[[0.324869129433,0,0],[0,4.21431974338,0],[0,0,1.46081112719]]`