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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 _get_historic_means(self, timeSeries):
 """Calculates the mean value for the history of the MeanAbsoluteScaledError. :param TimeSeries timeSeries: Original TimeSeries used to calculate the mean historic values. :return: Returns a list containing the historic means. :rtype: list """

        # calculate the history values
        historyLength = self._historyLength
        historicMeans = []
        append        = historicMeans.append

        # not most optimized loop in case of calculation operations
        for startIdx in xrange(len(timeSeries) - historyLength - 1):
            value = 0
            for idx in xrange(startIdx, startIdx + historyLength):
                value += abs(timeSeries[idx+1][1] - timeSeries[idx][1])

            append(value / float(historyLength))

        return historicMeans