[Python] Pandas sum by groupby, but exclude certain columns

What is the best way to do a groupby on a Pandas dataframe, but exclude some columns from that groupby? e.g. I have the following dataframe:

Code Country Item_Code Item Ele_Code Unit Y1961 Y1962 Y1963
2 Afghanistan 15 Wheat 5312 Ha 10 20 30
2 Afghanistan 25 Maize 5312 Ha 10 20 30
4 Angola 15 Wheat 7312 Ha 30 40 50
4 Angola 25 Maize 7312 Ha 30 40 50


I want to groupby the column Country and Item_Code and only compute the sum of the rows falling under the columns Y1961, Y1962 and Y1963. The resulting dataframe should look like this:

Code Country Item_Code Item Ele_Code Unit Y1961 Y1962 Y1963
2 Afghanistan 15 C3 5312 Ha 20 40 60
4 Angola 25 C4 7312 Ha 60 80 100


Right now I am doing this:

df.groupby('Country').sum()


However this adds up the values in the Item_Code column as well. Is there any way I can specify which columns to include in the sum() operation and which ones to exclude?

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