How to perform group-specific calculations using Pandas Dataframes

Question

I am trying to perform simple calculations on a Pandas dataframe. Refer to the example below:

df = pd.DataFrame({'A': [i < 5 == 0 for i in range(0, 10)], 
                   'B': [i for i in range(0, 10)]})

In this example, I want to create a new column 'C' that adds a group-specific counter offset to each value in column B so that I end up with df equaling:

       A    B   C
0   True    0   1
1   True    1   2
2   True    2   3
3   True    3   4
4   True    4   5
5   False   5   1
6   False   6   2
7   False   7   3
8   False   8   4
9   False   9   5

I have tried the following code but I don't get the results I want:

def add_1(b_column):
   return [i for i in range(0, len(b_column))]

df['C'] = df.groupby('A').apply(add_1)

Please advise.

Thanks