python - Sum up non-unique rows in DataFrame -

i have dataframe this:

id = [1,1,2,3] x1 = [0,1,1,2] x2 = [2,3,1,1]  df = pd.dataframe({'id':id, 'x1':x1, 'x2':x2})  df id  x1  x2 1   0   2 1   1   3 2   1   1 3   2   1 

some rows have same id. want sum such rows (over x1 , x2) obtain new dataframe unique ids:

df_new id  x1  x2 1   1   5 2   1   1 3   2   1 

an important detail real number of columns x1, x2,... large, cannot apply function requires manual input of column names.

as discussed can use pandas groupby function sum based on id value:

df.groupby(df.id).sum() # or df.groupby('id').sum() 

if need don't want id become index can:

df.groupby('id').sum().reset_index() # or df.groupby('id', as_index=false).sum()   # @john_gait