I am trying to get the residuals from a simple regression. This regressions is run by each Year and Group. This is what I have done. Howevevr, is there a way to get that residuals as a new columns along with original dataframe?

df=pd.DataFrame({'Name':['a','b','c','d','e','a','b','c','d','e','a','b','c','d','e'],
                 'Year':[2020,2020,2020,2020,2020,2021,2021,2021,2021,2021,2022,2022,2022,2022,2022],
                'Group':['H','L','N','N','N','H','L','N','N','N','H','L','N','N','N'],
                'Value':[0.3,0.2,0.3,0.1,0.1,0.2,0.3,0.2,0.2,0.1,0.4,0.1,0.1,0.3,0.1],
                'Mom':[5,1,3,5,2,1,1,3,6,4,4,7,8,3,2]})

def a(row):
    X = row['Value']  # independent variable
    y = row['Mom']   # dependent variable
    X = sm.add_constant(X)
    reg = sm.OLS(y, X).fit()
    
    return reg.resid

df.groupby(['Year','Group']).apply(a)

I can certainly append the above output to original dataframe but I am trying to achieve this by transform. I have tried this but it didn’t work out.

df.groupby(['Year','Group']).transform(a)