Nested loop - alternative solution - Python pandas

I have started learning python, and I wanted to ask if there is an alternative faster solution to the below nested loop:

for y in range(total_rows2):
    for x in range(total_rows1):
        if df2.iloc[y,0]==df1.iloc[x,0]:
            df1.iloc[x,1]=df1.iloc[x,1]+df2.iloc[y,17]

Basically, I have found the number of rows (total_rows1 and total_rows2) of two dataframes (df1 and df2). The first column of both dataframes (index=0) correspond to some IDs.

If the IDs of the two dataframes match, then I want to add the value of column 18 of df2(index 17, column name='Profit') to the second column of df1 (index=1, column name='Profit')

df2:

	ID	Profit
0	0104	0
1	0106	0
2	0107	0
3	0108	0

df1:

	ID	Loss	Profit
0	0104	100	230
1	0106	200	150
2	0108	150	120
3	0107	120	230
4	0109	100	400

Thanks!