Question

我有一个熊猫数据框，如下所示：

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我想创建一个名为+-----+--------+-------+ | Age | PhysID | PedID | +-----+--------+-------+ | 28 | 111 | 123 | | 26 | 111 | 123 | | 3 | 111 | 123 | +-----+--------+-------+的新列，如果DocID的值等于PhysID，否则的值等于Age>18。输出如下：

PedID

是否有使用某些内置函数而不是编写自己的函数的干净方法？谢谢！

Answer 1

使用np.where

df['NewId']=np.where(df.Age>18,df.PhysID,df.PedID)
df
   Age  PhysID  PedID  NewId
0   28     111    123    111
1   26     111    123    111
2    3     111    123    123

Answer 2

lambda函数可很好地解决此类问题

df = pd.DataFrame({'Age':[28,26,3],'PhysID':[111,111,111],'PedID':[123,123,123]})

df['DocId'] = df.apply(lambda x: x['PhysID'] if x['Age'] > 18 else x['PedID'], axis=1)

print（df）

根据熊猫数据框中其他列的条件和值创建新列

2 个答案: