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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 check_aggregate(df, variable, components=None, exclude_on_fail=False, multiplier=1, **kwargs):
 """Check whether the timeseries values match the aggregation of sub-categories Parameters df: IamDataFrame instance args: see IamDataFrame.check_aggregate() for details kwargs: passed to `df.filter()` """

    fdf = df.filter(**kwargs)
    if len(fdf.data) > 0:
        vdf = fdf.check_aggregate(variable=variable, components=components,
                                  exclude_on_fail=exclude_on_fail,
                                  multiplier=multiplier)
        df.meta['exclude'] |= fdf.meta['exclude']  # update if any excluded
        return vdf