The eigenvalues of non-Hermitian random matrices with independent, identically distributed entries are governed by the circular law.
We consider the eigenvalues of random matrices with independent entries but remove the assumption of identical distributions, allowing
entries to have different variances. We describe the eigenvalue density of such matrices under certain assumptions on the graph theoretic properties
on the connectivity of the variance profile.