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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 moving_tajima_d(ac, size, start=0, stop=None, step=None, min_sites=3):
 """Calculate the value of Tajima's D in moving windows of `size` variants. Parameters ac : array_like, int, shape (n_variants, n_alleles) Allele counts array. size : int The window size (number of variants). start : int, optional The index at which to start. stop : int, optional The index at which to stop. step : int, optional The number of variants between start positions of windows. If not given, defaults to the window size, i.e., non-overlapping windows. min_sites : int, optional Minimum number of segregating sites for which to calculate a value. If there are fewer, np.nan is returned. Defaults to 3. Returns ------- d : ndarray, float, shape (n_windows,) Tajima's D. Examples -------- array([0.1676558 , 2.01186954, 5.70029703]) """


    d = moving_statistic(values=ac, statistic=tajima_d, size=size, start=start, stop=stop,
                         step=step, min_sites=min_sites)
    return d