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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 box_cox(table):
 """ box-cox transform table """

    from scipy.stats import boxcox as bc
    t = []
    for i in table:
        if min(i) == 0:
            scale = min([j for j in i if j != 0]) * 10e-10
        else:
            scale = 0
        t.append(np.ndarray.tolist(bc(np.array([j + scale for j in i]))[0]))
    return t