def METHOD_NAME(self, year = None):
    target_source = self.target_source
    assert target_source in ["ines", "taxipp"], "les options possible pour source_cible sont ines ou taxipp"
    assert year is not None
    if target_source == "taxipp":
        taxipp_aggregates_file = Path(
            pkg_resources.get_distribution("openfisca-france_data").location,
            "openfisca_france_data",
            "assets",
            "aggregats",
            "taxipp",
            "agregats_tests_taxipp_2_0.xlsx"
            )
        df = (
            pd.read_excel(
                taxipp_aggregates_file,
                # "https://gitlab.com/ipp/partage-public-ipp/taxipp/-/blob/master/simulation/assets/agregats_tests_taxipp_2_0.xlsx",
                # engine = 'openpyxl'
                )
            .rename(columns = str.lower)
            .rename(columns = {"unnamed: 0": "description"})
            .dropna(subset = ["annee 2019", "annee 2018", "annee 2017", "annee 2016"], how = "all")
            )
        if f"annee {year}" not in df:
            return
        df = (
            df[["variable_openfisca", f"annee {year}"]]
            .dropna()
            .rename(columns = {
                "variable_openfisca": "variable",
                f"annee {year}": year,
                })
            )
        beneficiaries = (
            df.loc[df.variable.str.startswith("nombre")]
            .set_index("variable")
            .rename(index = lambda x : x.replace("nombre_", ""))
            .rename(columns = {year: "actual_beneficiaries"})
            ) / self.beneficiaries_unit
        amounts = (
            df.loc[~df.variable.str.startswith("nombre")]
            .set_index("variable")
            .rename(columns = {year: "actual_amount"})
            ) / self.amount_unit
        result = amounts.merge(beneficiaries, on = "variable", how = "outer").drop("PAS SIMULE")
    elif target_source == "ines":
        ines_aggregates_file = Path(
            pkg_resources.get_distribution("openfisca-france_data").location,
            "openfisca_france_data",
            "assets",
            "aggregats",
            "ines",
            f"ines_{year}.json"
            )
        with open(ines_aggregates_file, 'r') as f:
            data = json.load(f)
        result = pd.DataFrame(data['data']).drop('notes', axis = 1)
        result['actual_beneficiaries'] = result. actual_beneficiaries / self.beneficiaries_unit
        result['actual_amount'] = result. actual_amount / self.amount_unit
        result = result[["variable","actual_amount","actual_beneficiaries"]].set_index("variable")
    return result