Simulate a Markov chain modeling the evolution of a population

Markov chains are stochastic processes that undergo transitions from one state to another in a state space. They describe a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Transitions occur at every time step. Markov. These models are widely used in scientific and engineering applications.

Given this information (and after brushing up on Markov chains if needed), create a Markov chain, modeling the evolution of a population over time. Our solution will be written in Python for premium users.