def METHOD_NAME(self, data):
    """Aggregate county data to the HRR resolution.
    Note that counties are not strictly contained within HRRs. When a county
    spans boundaries, we report it with the same rate in each containing HRR,
    but with a sample size weighted by how much it overlaps that HRR.
    Args:
        data: dataframe aggregated to the daily-county resolution (all 7 cols expected)
    Returns:
        tuple of (data frame at daily-HRR resolution, geo_id column name)
    """
    data = self.gmpr.add_geocode(data,
                                 "fips",
                                 "hrr",
                                 from_col="PatCountyFIPS")
    data.drop(columns="PatCountyFIPS", inplace=True)
    ## do a weighted sum by the wpop column to get each HRR's contribution
    tmp = data.groupby(["ServiceDate", "hrr"])
    wtsum = lambda g: g["weight"].values @ g[Config.COUNT_COLS]
    data = tmp.apply(wtsum).reset_index()
    return data.groupby("hrr"), "hrr"