如果列中的值不為null，則在pandas中創建一個新的派生列

Question

我的輸入數據是這樣的

SL.NO   Name
1      KING  BATA
2   
3   
4     AGS
5     FORMULA GROWTH 
6   
7     Bag

產量

SL.NO   Name               Value
1     KING  BATA          Present
2                         Not Present
3                         Not Present
4   AGS                   Present
5   FORMULA GROWTH       Present
6                        Not Present
7   Bag                  Present

如何處理熊貓中的空值，空白值和垃圾值？

Answer 1

使用numpy.where ：

#If missing value is NaN
df['Value'] = np.where(df['Name'].isnull(), 'Present', 'Not Present')

要么：

#If missing value is empty string
df['Value'] = np.where(df['Name'].eq(''), 'Present', 'Not Present')

Answer 2

與pd.Categorical一起pd.Categorical ：

df

   SL.NO            Name
0      1       KING BATA
1      2                
2      3                
3      4             AGS
4      5  FORMULA GROWTH
5      6                
6      7             Bag

df['Value'] = pd.Categorical.from_codes(df.Name.astype(bool),
                              categories=['Not Present', 'Present'])
df

   SL.NO            Name        Value
0      1       KING BATA      Present
1      2                  Not Present
2      3                  Not Present
3      4             AGS      Present
4      5  FORMULA GROWTH      Present
5      6                  Not Present
6      7             Bag      Present

順便說一句，無論您缺少的值是NaN s， None還是'' ，它都可以工作，因為astype(bool)利用了這些值的虛假性：

df

   SL.NO            Name        Value
0      1       KING BATA      Present
1      2            None  Not Present
2      3            None  Not Present
3      4             AGS      Present
4      5  FORMULA GROWTH      Present
5      6            None  Not Present
6      7             Bag      Present