python numpy 创建数据集列 : only add value based on condition otherwise null

Question

我尝试创建列终止日期。但只有当标志取消或失效设置为是时，列终止日期才应包含生效日期，否则为空。对于这三种方法，我收到以下错误消息。

df['Termination_Date'] = np.where((df['Cancellations'] == 'Yes') | (df['Lapses'] == 'Yes'), df['Effective Date'])
ValueError: either both or neither of x and y should be given

df['Termination_Date'] = np.where((df['Cancellations'] == 'Yes') | (df['Lapses'] == 'Yes'), df['Effective Date'], "")
TypeError: invalid type promotion

df['Termination_Date'] = np.where((df['Cancellations'] == 'Yes') | (df['Lapses'] == 'Yes'), df['Effective Date'], np.nan)
TypeError: invalid type promotion

谢谢

Answer 1

可以与 Series.where 一起使用？

示例:

df = pd.DataFrame({
         'Effective Date':pd.date_range('2019-01-01', periods=6),
         'Cancellations':['Yes'] * 4 + ['No'] * 2,
         'Lapses':['yes'] * 2 + ['No'] * 4,

})

df['Termination_Date'] = df['Effective Date'].where((df['Cancellations'] == 'Yes') | 
                                                     (df['Lapses'] == 'Yes')) 

或者:

m = (df['Cancellations'] == 'Yes') | (df['Lapses'] == 'Yes')
df.loc[m, 'Termination_Date'] = df['Effective Date']

---

print (df)
  Effective Date Cancellations Lapses Termination_Date
0     2019-01-01           Yes    yes       2019-01-01
1     2019-01-02           Yes    yes       2019-01-02
2     2019-01-03           Yes     No       2019-01-03
3     2019-01-04           Yes     No       2019-01-04
4     2019-01-05            No     No              NaT
5     2019-01-06            No     No              NaT