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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 mad(a, normalize=True, axis=0):
 """ Median Absolute Deviation along given axis of an array. Parameters a : array-like Input array. normalize : boolean. If True, scale by a normalization constant (~0.67) axis : int, optional The defaul is 0. Can also be None. Returns ------- mad : float mad = median(abs(a - median(a))) / c References .. [1] https://en.wikipedia.org/wiki/Median_absolute_deviation Examples -------- 2.965204437011204 2.0 """

    from scipy.stats import norm
    a = np.asarray(a)
    c = norm.ppf(3 / 4.) if normalize else 1
    center = np.apply_over_axes(np.median, a, axis)
    return np.median((np.fabs(a - center)) / c, axis=axis)