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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 lambda_A_calc(classes, table, P, POP):
 """ Calculate Goodman and Kruskal's lambda A. :param classes: confusion matrix classes :type classes : list :param table: confusion matrix table :type table : dict :param P: condition positive :type P : dict :param POP: population :type POP : int :return: Goodman and Kruskal's lambda A as float """

    try:
        result = 0
        maxreference = max(list(P.values()))
        length = POP
        for i in classes:
            col = []
            for col_item in table.values():
                col.append(col_item[i])
            result += max(col)
        result = (result - maxreference) / (length - maxreference)
        return result
    except Exception:
        return "None"