@staticmethod
def __scale_with_column_range(data, column_upper, column_lower, mean, std, process_cols_list):
    for i in process_cols_list:
        value = data.features[i]
        if (value > column_upper[i]):
            value = column_upper[i]
        elif (value < column_lower[i]):
            value = column_lower[i]
        data.features[i] = np.around(((value - mean[i]) / std[i]), 6)
    return data
@staticmethod
def __scale_with_column_range(data, column_upper, column_lower, mean, std, process_cols_list):
    for i in process_cols_list:
        value = data.features[i]
        if (value > column_upper[i]):
            value = column_upper[i]
        elif (value < column_lower[i]):
            value = column_lower[i]
        data.features[i] = np.around(((value - mean[i]) / std[i]), 6)
    return data