根据某一列过滤行，然后检查另一列的值是否在Python的特定列表中

给定以下玩具构建数据，我想检查何时type == 'other'，在数据框中是否存在一些不规则的值（表示inHall或Parking space）name。

    id    type                          name
0    1  office  Hessel, Macejkovic and Nader
1    2  office                Stiedemann LLC
2    3  office                     Grant Ltd
3    4  office                Anderson Group
4    5  retail                   MacDanald's
5    6  retail                      Wallmart
6    7  retail                      Wallmart
7    8   other                          Hall
8    9   other                 Parking space
9   10   other                 Parking space
10  11   other                   Roberts PLC

对于上面的数据集，我希望它创建一个新列indication并返回N最后一行，因为Roberts PLC它不在中['Hall', 'Parking space']。

    id    type                          name indication
0    1  office  Hessel, Macejkovic and Nader        NaN
1    2  office                Stiedemann LLC        NaN
2    3  office                     Grant Ltd        NaN
3    4  office                Anderson Group        NaN
4    5  retail                   MacDanald's        NaN
5    6  retail                      Wallmart        NaN
6    7  retail                      Wallmart        NaN
7    8   other                          Hall        NaN
8    9   other                 Parking space        NaN
9   10   other                 Parking space        NaN
10  11   other                   Roberts PLC          N

我使用过的代码需要编辑：

m = df1.loc[df1['type'].isin(['other'])]
if m['name'].str.contains('Hall|Parking space', na = False).any():
    print('')
else:
    print('N')

感谢您提前的帮助。

加：

对于打印指示：

if (df["type"].eq("other")) & (~df["name"].str.contains('Hall|Parking space', na = False).any()):
    print('Other type data has irregular data')
else:
    print('No irregular data found in other type data')

出：

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().