In [9]:

    

import pandas as pd
import numpy as np

dates = pd.date_range('20161010', periods=6)
df = pd.DataFrame(np.arange(24).reshape((6,4)),index=dates, columns=['A','B','C','D'])

df.iloc[2,2] = 1111
df.loc['20161011', 'D'] = 2222
df


    

    
Out[9]:






  

    

      

      
A
      
B
      
C
      
D
    
  
  

    

      
2016-10-10
      
0
      
1
      
2
      
3
    
    

      
2016-10-11
      
4
      
5
      
6
      
2222
    
    

      
2016-10-12
      
8
      
9
      
1111
      
11
    
    

      
2016-10-13
      
12
      
13
      
14
      
15
    
    

      
2016-10-14
      
16
      
17
      
18
      
19
    
    

      
2016-10-15
      
20
      
21
      
22
      
23
    
  

In [14]:

    

df['E'] = np.nan
df['G'] = pd.Series([1,2,3,4,5,6],index=pd.date_range('20161010', periods=6))
df


    

    
Out[14]:






  

    

      

      
A
      
B
      
C
      
D
      
E
      
G
    
  
  

    

      
2016-10-10
      
0
      
1
      
2
      
3
      
NaN
      
1
    
    

      
2016-10-11
      
4
      
5
      
6
      
2222
      
NaN
      
2
    
    

      
2016-10-12
      
8
      
9
      
1111
      
11
      
NaN
      
3
    
    

      
2016-10-13
      
12
      
13
      
14
      
15
      
NaN
      
4
    
    

      
2016-10-14
      
16
      
17
      
18
      
19
      
NaN
      
5
    
    

      
2016-10-15
      
20
      
21
      
22
      
23
      
NaN
      
6