in datasets/census_bureau_international/pipelines/_images/run_csv_transform_kub_midyear_population_age_sex/csv_transform.py [0:0]
def reorder_headers(df: pd.DataFrame) -> pd.DataFrame:
logging.info("Reordering headers..")
df = df[
[
"country_code",
"country_name",
"year",
"sex",
"max_age",
"population_age_0",
"population_age_1",
"population_age_2",
"population_age_3",
"population_age_4",
"population_age_5",
"population_age_6",
"population_age_7",
"population_age_8",
"population_age_9",
"population_age_10",
"population_age_11",
"population_age_12",
"population_age_13",
"population_age_14",
"population_age_15",
"population_age_16",
"population_age_17",
"population_age_18",
"population_age_19",
"population_age_20",
"population_age_21",
"population_age_22",
"population_age_23",
"population_age_24",
"population_age_25",
"population_age_26",
"population_age_27",
"population_age_28",
"population_age_29",
"population_age_30",
"population_age_31",
"population_age_32",
"population_age_33",
"population_age_34",
"population_age_35",
"population_age_36",
"population_age_37",
"population_age_38",
"population_age_39",
"population_age_40",
"population_age_41",
"population_age_42",
"population_age_43",
"population_age_44",
"population_age_45",
"population_age_46",
"population_age_47",
"population_age_48",
"population_age_49",
"population_age_50",
"population_age_51",
"population_age_52",
"population_age_53",
"population_age_54",
"population_age_55",
"population_age_56",
"population_age_57",
"population_age_58",
"population_age_59",
"population_age_60",
"population_age_61",
"population_age_62",
"population_age_63",
"population_age_64",
"population_age_65",
"population_age_66",
"population_age_67",
"population_age_68",
"population_age_69",
"population_age_70",
"population_age_71",
"population_age_72",
"population_age_73",
"population_age_74",
"population_age_75",
"population_age_76",
"population_age_77",
"population_age_78",
"population_age_79",
"population_age_80",
"population_age_81",
"population_age_82",
"population_age_83",
"population_age_84",
"population_age_85",
"population_age_86",
"population_age_87",
"population_age_88",
"population_age_89",
"population_age_90",
"population_age_91",
"population_age_92",
"population_age_93",
"population_age_94",
"population_age_95",
"population_age_96",
"population_age_97",
"population_age_98",
"population_age_99",
"population_age_100",
]
]
return df