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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 lkruskalwallish(*args):
 """ The Kruskal-Wallis H-test is a non-parametric ANOVA for 3 or more groups, requiring at least 5 subjects in each group. This function calculates the Kruskal-Wallis H-test for 3 or more independent samples and returns the result. Usage: lkruskalwallish(*args) Returns: H-statistic (corrected for ties), associated p-value """

    args = list(args)
    n = [0]*len(args)
    all = []
    n = [len(_) for _ in args]
    for i in range(len(args)):
        all = all + args[i]
    ranked = rankdata(all)
    T = tiecorrect(ranked)
    for i in range(len(args)):
        args[i] = ranked[0:n[i]]
        del ranked[0:n[i]]
    rsums = []
    for i in range(len(args)):
        rsums.append(sum(args[i])**2)
        rsums[i] = rsums[i] / float(n[i])
    ssbn = sum(rsums)
    totaln = sum(n)
    h = 12.0 / (totaln*(totaln+1)) * ssbn - 3*(totaln+1)
    df = len(args) - 1
    if T == 0:
        raise ValueError('All numbers are identical in lkruskalwallish')
    h = h / float(T)
    return h, chisqprob(h,df)