def METHOD_NAME():
    df_in = read_csv_and_index_fips_date(
        "fips,state,aggregate_level,county,m1,date,foo\n"
        "55005,ZZ,county,North County,1,2020-05-01,11\n"
        "55005,ZZ,county,North County,2,2020-05-02,22\n"
        "55005,ZZ,county,North County,3,2020-05-03,33\n"
        "55005,ZZ,county,North County,0,2020-05-04,0\n"
        "55007,ZZ,county,South County,0,2020-05-01,0\n"
        "55007,ZZ,county,South County,0,2020-05-02,0\n"
        "55007,ZZ,county,South County,3,2020-05-03,44\n"
        "55007,ZZ,county,South County,4,2020-05-04,55\n"
        "55,ZZ,state,Grand State,41,2020-05-01,66\n"
        "55,ZZ,state,Grand State,43,2020-05-03,77\n"
    ).reset_index()
    ts_in = MultiRegionDataset.from_fips_timeseries_df(df_in)
    agg = statistical_areas.CountyToCBSAAggregator(
        county_map={"55005": "10100", "55007": "10100"},
        cbsa_title_map={"10100": "Stat Area 1"},
        aggregations=[],
    )
    ts_out = agg.aggregate(ts_in)
    assert ts_out.groupby_region().ngroups == 1
    ts_cbsa = ts_out.get_one_region(Region.from_cbsa_code("10100"))
    assert ts_cbsa.date_indexed["m1"].to_dict() == {
        pd.to_datetime("2020-05-01"): 1,
        pd.to_datetime("2020-05-02"): 2,
        pd.to_datetime("2020-05-03"): 6,
        pd.to_datetime("2020-05-04"): 4,
    }