Circular law states the eigenvalues of a matrix with random entries of mean 0 and variance 1/n are approximately uniformly distributed in the unit disk of the complex plane. To see this, create a random matrix:

n = 1000
x = randomu(seed, n, n) - 0.5
x *= sqrt(12.0 / n)

Find the eigenvalues:

eigenvalues = la_eigenproblem(x, eigenvectors=eigenvectors)

Plot them:

plot, real_part(eigenvalues), imaginary(eigenvalues), $
      psym=3, $
      xstyle=1, xrange=[-1.5, 1.5], $
      ystyle=1, yrange=[-1.5, 1.5]

This gives a plot like below:

Via the excellent John D. Cook blog. I recommend reading his site if you are interested in a combination of mathematics and Python.