修改特定值以外的列值无效

Question

我有下面的数据帧，需要修改专业列，除非值有博士。

id  firstname   lastname    email   profession
0   100 Ekaterina   Skell   [e-mail] developer
1   101 Judy    Vernier [e-mail]    police officer
2   102 Tarra   Diann   [e-mail] police officer
3   103 Odessa  Maxi    [e-mail] firefighter
4   104 Mallory Peonir  [e-mail]  firefighter
5   105 Nataline    Hoenack [e-mail]    doctor
6   106 Dude    Adrienne    [e-mail]   developer
7   107 Caressa Meli    [e-mail]    doctor
8   108 Zaria   Carey   [e-mail] firefighter
9   109 Harmonia    Seumas  [e-mail] worker

我试过的是

if src[src['profession'].isin(['doctor'])]:
src['profession'] = src['profession'].astype(str)+'-Done'

但我的错误越来越少。

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

我如何获得以下输出(如果值有doctor，则不应附加)

id  firstname   lastname    email   profession
0   100 Ekaterina   Skell   [e-mail] developer-Done
1   101 Judy    Vernier [e-mail]    police officer-Done
2   102 Tarra   Diann   [e-mail] police officer-Done
3   103 Odessa  Maxi    [e-mail] firefighter-Done
4   104 Mallory Peonir  [e-mail]  firefighter-Done
5   105 Nataline    Hoenack [e-mail]    doctor
6   106 Dude    Adrienne    [e-mail]   developer-Done
7   107 Caressa Meli    [e-mail]    doctor
8   108 Zaria   Carey   [e-mail] firefighter-Done
9   109 Harmonia    Seumas  [e-mail] worker-Done

Answer 1

通过~:使用具有反向掩码的DataFrame.loc

#if need compare one scalar value
m = src['profession'].eq('doctor')
#if need compare by list of values
m = src['profession'].isin(['doctor'])
src.loc[~m, 'profession'] = src.loc[~m, 'profession'].astype(str)+'-Done'

或numpy.where:

src['profession'] = np.where(m, src['profession'], src['profession'].astype(str)+'-Done')

如果需要100%所有字符串：

s = src['profession'].astype(str)
src['profession'] = np.where(m, s, s+'-Done')