def METHOD_NAME():
    # load in the data
    country_wk = pd.read_csv(
        f"{BASE_URL}/export_country.csv",
        usecols=[
            "iso3c",
            "date",
            "estimated_daily_excess_deaths",
            "estimated_daily_excess_deaths_ci_95_top",
            "estimated_daily_excess_deaths_ci_95_bot",
        ],  # type: ignore
    )
    country_wk_100k = pd.read_csv(
        f"{BASE_URL}/export_country_per_100k.csv",
        usecols=[
            "iso3c",
            "date",
            "estimated_daily_excess_deaths_per_100k",
            "estimated_daily_excess_deaths_ci_95_top_per_100k",
            "estimated_daily_excess_deaths_ci_95_bot_per_100k",
        ],  # type: ignore
    )
    country_cum = pd.read_csv(
        f"{BASE_URL}/export_country_cumulative.csv",
        usecols=[
            "iso3c",
            "date",
            "cumulative_estimated_daily_excess_deaths",
            "cumulative_estimated_daily_excess_deaths_ci_95_top",
            "cumulative_estimated_daily_excess_deaths_ci_95_bot",
        ],  # type: ignore
    )
    country_cum_100k = pd.read_csv(
        f"{BASE_URL}/export_country_per_100k_cumulative.csv",
        usecols=[
            "iso3c",
            "date",
            "cumulative_estimated_daily_excess_deaths_per_100k",
            "cumulative_estimated_daily_excess_deaths_ci_95_top_per_100k",
            "cumulative_estimated_daily_excess_deaths_ci_95_bot_per_100k",
        ],  # type: ignore
    )
    # this file tells whether reported data is available
    reported = pd.read_csv(f"{BASE_URL}/output-for-interactive/by_location_full_data.csv")
    report_select = reported[reported["type"] == "daily_excess_deaths"][["iso3c", "date", "known_excess_deaths"]]
    # get rid of NA rows
    report_select = report_select[report_select["iso3c"].notna()]
    # merge all the data
    country_wk_merge = pd.merge(country_wk, country_wk_100k, on=["iso3c", "date"], how="outer")
    country_cum_merge = pd.merge(country_cum, country_cum_100k, on=["iso3c", "date"], how="outer")
    country_almost = pd.merge(country_cum_merge, country_wk_merge, on=["iso3c", "date"], how="outer")
    country_all = pd.merge(country_almost, report_select, on=["iso3c", "date"], how="outer")
    # the most recent date can have null known_excess_deaths, fill them with False
    country_all["known_excess_deaths"] = country_all["known_excess_deaths"].fillna(False)
    return country_all