Complex systems, and in particular random neural networks, are often described by randomly interacting dynamical systems with no specific symmetry. In that context, characterizing the number of relevant directions necessitates fine estimates on the Ginibre ensemble. In this Letter, we compute analytically the probability distribution of the number of eigenvalues $N_R$ with modulus greater than $R$ (the index) of a large $N\times N$ random matrix in the real or complex Ginibre ensemble. We show that the fraction $N_R/N=p$ has a distribution scaling as $\exp(-\beta N^2 \psi_R(p))$ with $\beta=1$ (respectively $\beta=1/2$) for the complex (resp. real) Ginibre ensemble. For any $p\in[0,1]$, the equilibrium spectral densities as well as the rate function $\psi_R(p)$ are explicitly derived. This function displays a third order phase transition at the critical (minimum) value $p^*_R=1-R^2$, associated to a phase transition of the Coulomb gas. We deduce that, in the central regime, the fluctuations of the index $N_R$ around its typical value $p^*_R N$ scale as $N^{1/3}$.