pandas DataFrameの各カラムに対し、単一の式から異なる処理（＝計算式）を呼び出すクラスの作成

from enum import Enum

class DataCol1:
    @staticmethod
    def clean(sr:pd.Series):
        return sr+100

class DataCol2:
    @classmethod
    def clean(cls, sr:pd.Series):
        return sr*100

class DataCleansing(Enum):
    col_1 = DataCol1
    col_2 = DataCol2

    @classmethod
    def clean(cls, col:str, sr:pd.Series):
        for e in DataCleansing:
            if e.name == col:
                return e.value.clean(sr=sr)

        raise ValueError('{} is invalid column.'.format(col))

DataCleansing.clean(col='col_1', sr=_df['col_1'])
DataCleansing.clean(col='col_2', sr=_df['col_2'])
DataCleansing.clean(col='col_3', sr=_df['col_3'])
# ...
# -> for文、内包表記化が可能

def calc_col1(sr):
    return sr + 100

def calc_col2(sr, num):
    return sr - 100 + num


class TestClass:
    clean = {
        'col_1': calc_col1,
        'col_2': calc_col2
    }

TestClass.clean['col_1'](sr=_df['col_1'])
TestClass.clean['col_2'](sr=_df['col_2'], num=10)
# ...

def clean1(sr):
    return sr + 100

def clean2(sr):
    return sr - 100

def clean(col, sr):
    col_to_func = {
        "col1": clean1,
        "col2": clean2
    }
    return col_to_func[col](sr)