def METHOD_NAME(df_tot: pd.DataFrame) -> pd.DataFrame:
    """
    Create the total homicides dataframe where we will have total homicides/homicide rate
    disaggregated by age and sex
    """
    # To escape the dataframe slice warnings
    df_tot = df_tot.copy(deep=True)
    # There are some duplicates when sex is unknown so let's remove those rows
    df_tot = df_tot[df_tot["sex"] != "Unknown"]
    # Make it more obvious what total age and total sex means
    df_tot["age"] = df_tot["age"].map({"Total": "All ages"}, na_action="ignore").fillna(df_tot["age"])
    df_tot["sex"] = df_tot["sex"].map({"Total": "Both sexes"}, na_action="ignore").fillna(df_tot["sex"])
    df_tot = pivot_and_format_df(
        df_tot,
        drop_columns=["region", "subregion", "indicator", "dimension", "category", "source"],
        pivot_index=["country", "year"],
        pivot_values=["value"],
        pivot_columns=["sex", "age", "unit_of_measurement"],
    )
    return df_tot