In [1]:

    

import pandas as pd


    

In [2]:

    

s_org = pd.Series(['aaa@xxx.com', 'bbb@yyy.com', 'ccc@zzz.com', 'ddd'], index=['A', 'B', 'C', 'D'])
print(s_org)


    

    




A    aaa@xxx.com
B    bbb@yyy.com
C    ccc@zzz.com
D            ddd
dtype: object

In [3]:

    

df = s_org.str.extract('(.+)@(.+)\.(.+)', expand=True)
print(df)


    

    




     0    1    2
A  aaa  xxx  com
B  bbb  yyy  com
C  ccc  zzz  com
D  NaN  NaN  NaN

In [4]:

    

df = s_org.str.extract('(.+)@(.+)\.(.+)', expand=False)
print(df)


    

    




     0    1    2
A  aaa  xxx  com
B  bbb  yyy  com
C  ccc  zzz  com
D  NaN  NaN  NaN

In [5]:

    

df_single = s_org.str.extract('(\w+)', expand=True)
print(df_single)
print(type(df_single))


    

    




     0
A  aaa
B  bbb
C  ccc
D  ddd
<class 'pandas.core.frame.DataFrame'>

In [6]:

    

s = s_org.str.extract('(\w+)', expand=False)
print(s)
print(type(s))


    

    




A    aaa
B    bbb
C    ccc
D    ddd
dtype: object
<class 'pandas.core.series.Series'>

In [7]:

    

df_name = s_org.str.extract('(?P<local>.*)@(?P<second_LD>.*)\.(?P<TLD>.*)', expand=True)
print(df_name)


    

    




  local second_LD  TLD
A   aaa       xxx  com
B   bbb       yyy  com
C   ccc       zzz  com
D   NaN       NaN  NaN