python - 将从一列中提取以 "Unit"开头的字符串并将其复制到新列 : Pandas

Question

下面是我的输入数据的样子。我想使用 pandas/python/regex 将所有以“Unit”开头的字符串提取到与第二列中单词的位置相对应的新列中。任何帮助将不胜感激。

Input:

   A
MARYLAND
Unit6
Unit7
Unit8
NEW SECTOR
Unit1
Unit2
NORTH SECTOR
Unit1
Unit2
PVT SECTOR
PUBLIC SECTOR
Unit1
Unit2
CENTRAL SECTOR
THERMAL
SOUTH SECTOR
Unit1
Unit2
Unit3
ACCOUNT SECTOR
DOLBY DIGITAL
WASHINGTON


Output:

   A              B
MARYLAND            
Unit6           Unit6
Unit7           Unit7
Unit8           Unit8
NEW SECTOR          
Unit1           Unit1
Unit2           Unit2
NORTH SECTOR            
Unit1           Unit1
Unit2           Unit2
PVT SECTOR          
PUBLIC SECTOR           
Unit1           Unit1
Unit2           Unit2
CENTRAL SECTOR          
THERMAL         
SOUTH SECTOR            
Unit1           Unit1
Unit2           Unit2
Unit3           Unit3
ACCOUNT SECTOR          
DOLBY DIGITAL           
WASHINGTON          

最后，现在“Unit”字符串已复制到新列，我想从 A 列中删除这些值:

    A            B
MARYLAND            
                Unit6
                Unit7
                Unit8
NEW SECTOR          
                Unit1
                Unit2
NORTH SECTOR            
                Unit1
                Unit2
PVT SECTOR          
PUBLIC SECTOR           
                Unit1
                Unit2
CENTRAL SECTOR          
THERMAL         
SOUTH SECTOR            
                Unit1
                Unit2
                Unit3
ACCOUNT SECTOR          
DOLBY DIGITAL           
WASHINGTON  

Answer 1

使用str.extract和 fillna :

df['B'] = df['A'].str.extract('(^Unit\d+)')
df.loc[df['B'].notnull(),'A'] = ''
df['B'].fillna('',inplace=True)

print(df)
                 A      B
0         MARYLAND       
1                   Unit6
2                   Unit7
3                   Unit8
4       NEW SECTOR       
5                   Unit1
6                   Unit2
7     NORTH SECTOR       
8                   Unit1
9                   Unit2
10      PVT SECTOR       
11   PUBLIC SECTOR       
12                  Unit1
13                  Unit2
14  CENTRAL SECTOR       
15         THERMAL       
16    SOUTH SECTOR       
17                  Unit1
18                  Unit2
19                  Unit3
20  ACCOUNT SECTOR       
21   DOLBY DIGITAL       
22      WASHINGTON