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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _nbinom_ztrunc_p(mu, k_agg):
 """ Calculates p parameter for truncated negative binomial Function given in Sampford 1955, equation 4 Note that omega = 1 / 1 + p in Sampford """


        p_eq = lambda p, mu, k_agg: (k_agg * p) / (1 - (1 + p)**-k_agg) - mu

        # The upper bound needs to be large. p will increase with increasing mu
        # and decreasing k_agg
        p = optim.brentq(p_eq, 1e-10, 1e10, args=(mu, k_agg))
        return p