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We introduce `PI-Entropy' $Π(\tildeρ)$ (the Permutation entropy of an Indexed ensemble) to quantify mixing due to complex dynamics for an ensemble $ρ$ of different initial states evolving under identical dynamics. We find that $Π(\tildeρ)$ acts as an excellent proxy for the thermodynamic entropy $S(ρ)$ but is much more computationally efficient. We study 1-D and 2-D iterative maps and find that $Π(\tildeρ)$ dynamics distinguish a variety of system time scales and track global loss of information as the ensemble relaxes to equilibrium. There is a universal S-shaped relaxation to equilibrium for generally chaotic systems, and this relaxation is characterized by a \emph{shuffling} timescale that correlates with the system's Lyapunov exponent. For the Chirikov Standard Map, a system with a mixed phase space where the chaos grows with nonlinear kick strength $K$, we find that for high $K$, $Π(\tildeρ)$ behaves like the uniformly hyperbolic 2-D Cat Map. For low $K$ we see periodic behavior with a relaxation envelope resembling those of the chaotic regime, but with frequencies that depend on the size and location of the initial ensemble in the mixed phase space as well as $K$. We discuss how $Π(\tildeρ)$ adapts to experimental work and its general utility in quantifying how complex systems change from a low entropy to a high entropy state.