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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 quantile(y, k=4):
 """ Calculates the quantiles for an array Parameters y : array (n,1), values to classify k : int number of quantiles Returns ------- q : array (n,1), quantile values Examples -------- array([249.75, 499.5 , 749.25, 999. ]) array([333., 666., 999.]) Note that if there are enough ties that the quantile values repeat, we collapse to pseudo quantiles in which case the number of classes will be less than k 140 array([1., 3.]) """


    w = 100. / k
    p = np.arange(w, 100 + w, w)
    if p[-1] > 100.0:
        p[-1] = 100.0
    q = np.array([stats.scoreatpercentile(y, pct) for pct in p])
    q = np.unique(q)
    k_q = len(q)
    if k_q < k:
        Warn('Warning: Not enough unique values in array to form k classes',
             UserWarning)
        Warn('Warning: setting k to %d' % k_q, UserWarning)
    return q