熊猫-根据多个条件添加一列

Question

尝试基于两个互斥条件向df添加布尔列：

1. df['Type'] == 'CMBX'
2. df['SubType'].isin(['EM','NAHY'])

他们分开工作

df['Px Quoted'] = np.where(df['Type'] =='CMBX', True, False)
df[df['Type']=='CMBX'].head(5)
Out[72]: 
  Batch  Type SubType  Px Quoted
0   NaN  CMBX               True
1   NaN  CMBX               True
2   NaN  CMBX               True
3   NaN  CMBX               True
4   NaN  CMBX               True

或

df['Px Quoted'] = np.where(df['SubType'].isin(['EM','NAHY']), True, False)

df[df['SubType']=='EM'].head(5)
Out[74]: 
     Batch Type SubType  Px Quoted
21  NY1530  CDX      EM       True
29  NY1530  CDX      EM       True
36  NY1530  CDX      EM       True
43  NY1530  CDX      EM       True
50  NY1530  CDX      EM       True

但以下内容不

df['Px Quoted'] = np.where(df['Type'] =='CMBX' or df['SubType'].isin(['EM','NAHY']), True, False)

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

不确定CMBX类型为何不能包含子类型['EM','NAHY']中的任何内容，为什么会造成歧义？是因为其子类型为空？

Answer 1

对于np.where，您需要使用按位运算符：

df['Px Quoted'] = np.where((df['Type'] =='CMBX') | (df['SubType'].isin(['EM','NAHY'])), True, False)

在这里，我将or更改为|