Pandas merge column duplicate and sum value
You may use

df2 = df.groupby(['address']).sum()

or

df2 = df.groupby(['address']).agg('sum')

If there are columns other than balances that you want to peak only the first or max value,  or do mean instead of sum, you can go as follows:

d = {'address': ["A", "A", "B"], 'balances': [30, 40, 50], 'sessions': [2, 3, 4]} 
df = pd.DataFrame(data=d) 
df2 = df.groupby(['address']).agg({'balances': 'sum', 'sessions': 'mean'})


That outputs

         balances   sessions
address       
A              70       2.5  
B              50       4.0


You may add as_index = False to groupby arguments to have:

  address  balances  sessions
0       A        70       2.5
1       B        50       4.0