每组只保留一行drop_duplicates，计算cumsum和map的值：

df['CumulativeTotal'] = df['group'].map(df.drop_duplicates(subset='group')
                                          .set_index('group')['weeklyTotal']
                                          .cumsum()
                                       )

或者，使用mask和duplicated：

df['CumulativeTotal'] = (df['weeklyTotal']
                         .mask(df['group'].duplicated(), 0)
                         .cumsum()
                        )

输出：

group  weeklyTotal  CumulativeTotal
0     A            1                1
1     A            1                1
2     A            1                1
3     B            3                4
4     B            3                4
5     B            3                4
6     C            2                6
7     C            2                6
8     C            2                6

这里是另一种方法：

m = df['group'].ne(df['group'].shift())
m.mul(df['weeklyTotal']).cumsum()

输出：

0    1
1    1
2    1
3    4
4    4
5    4
6    6
7    6
8    6