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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_timeseries_values_for_indicators( self, resolution: str = "month", months: Iterable[int] = range(6, 9) ):
 """ Attach timeseries to indicators, for performing Bayesian inference. """

        if resolution == "month":
            funcs = [
                partial(get_indicator_value, month=month) for month in months
            ]
        else:
            raise NotImplementedError(
                "Currently, only the 'month' resolution is supported."
            )

        for n in self.nodes(data=True):
            for indicator in n[1]["indicators"].values():
                indicator.timeseries = [
                    func(indicator, year="2017")[0] for func in funcs
                ]
                if len(set(indicator.timeseries)) == 1:
                    indicator.timeseries = None