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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 ratio_value_number_to_time_series_length(x):
 """ Returns a factor which is 1 if all values in the time series occur only once, and below one if this is not the case. In principle, it just returns # unique values / # values :param x: the time series to calculate the feature of :type x: numpy.ndarray :return: the value of this feature :return type: float """

    if not isinstance(x, (np.ndarray, pd.Series)):
        x = np.asarray(x)
    if x.size == 0:
        return np.nan

    return np.unique(x).size / x.size