数据帧应用（map）函数类型

Question

有人能用这段代码指出我的错误吗：

groupIds = allData.drop_duplicates('GroupID').set_index('Ticket')['GroupID']

allData.loc[(allData['SexGroup']!='Man') & (allData['GroupID']=='Alone'), 'GroupID'].apply(lambda x: x['Ticket'].map(groupIds).fillna('Alone'))

错误是：

Exception has occurred: TypeError
string indices must be integers

谢谢

编辑：

数据

             Survived  Pclass                                               Name     Sex   Age  SibSp  Parch            Ticket     Fare Cabin Embarked Title SexGroup    Surname     TicketShort  FamilySize  Alone  IsWomanOrChild  SurnameFreq GroupID
PassengerId
1                 0.0       3                            Braund, Mr. Owen Harris    male  22.0      1      0         A/5 21171   7.2500   NaN        S    Mr      Man     Braund         A/5 211           2  False           False            0   Alone
2                 1.0       1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1      0          PC 17599  71.2833   C85        C   Mrs    Woman    Cumings          PC 175           2  False            True            1   Alone
3                 1.0       3                             Heikkinen, Miss. Laina  female  26.0      0      0  STON/O2. 3101282   7.9250   NaN        S  Miss    Woman  Heikkinen  STON/O2. 31012           1   True            True            1   Alone
4                 1.0       1       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1      0            113803  53.1000  C123        S   Mrs    Woman   Futrelle            1138           2  False            True            1   Alone
5                 0.0       3                           Allen, Mr. William Henry    male  35.0      0      0            373450   8.0500   NaN        S    Mr      Man      Allen            3734           1   True           False            1   Alone

编辑2：

代码应该遍历所有GroupID，其中性别是女性，当前GroupID是“单独的”。然后，如果满足这些条件，则对于该行，检查“Ticket”值是否出现在“Ticket”列的其他位置。如果是，则返回该事件的GroupID。如果没有，就让它“单独”吧

Answer 1

对任何想做类似事情的人来说，这对我来说都很有用：

allData.loc[(allData['SexGroup']!='Man') & (allData['GroupID']=='Alone'), 'GroupID'] = allData['Ticket'].map(groupIds).fillna('Alone')