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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 MakePoissonPmf(lam, high, step=1):
 """Makes a PMF discrete approx to a Poisson distribution. lam: parameter lambda in events per unit time high: upper bound of the Pmf returns: normalized Pmf """

    pmf = Pmf()
    for k in xrange(0, high + 1, step):
        p = EvalPoissonPmf(k, lam)
        pmf.Set(k, p)
    pmf.Normalize()
    return pmf