def METHOD_NAME():
    """load gapminder dataset's table only with former countries."""
    tb = Dataset(DATASET_GAPMINDER_SYSTEMA_GLOBALIS)["total_population_with_projections"]
    # reset index
    tb = tb.reset_index()
    # add source
    tb["source"] = SOURCE_NAME
    # filter countries
    msk = tb["geo"].isin(FORMER_COUNTRIES)
    tb = tb[msk]
    # rename countries
    tb["country"] = tb["geo"].map({code: data["name"] for code, data in FORMER_COUNTRIES.items()})
    # columns
    tb = tb.rename(columns={"time": "year", "total_population_with_projections": "population"})
    # filter countries
    for _, data in FORMER_COUNTRIES.items():
        country_name = data["name"]
        end_year = data["end"]
        tb = tb[-((tb["country"] == country_name) & (tb["year"] > end_year))]
    # output columns
    tb = tb[["country", "year", "population", "source"]]
    # reset index
    tb = tb.reset_index(drop=True)
    return tb