In [1]:

    

import numpy as np
import pandas as pd
from pandas import Series,DataFrame


    

In [2]:

    

df1 = DataFrame(np.arange(8).reshape(2,4),
                index=pd.Index(['LA','SF'],name='city'),
                columns=pd.Index(['A','B','C','D'],name='letters'))
df1


    

    
Out[2]:






  

    

      
letters
      
A
      
B
      
C
      
D
    
    

      
city
      

      

      

      

    
  
  

    

      
LA
      
0
      
1
      
2
      
3
    
    

      
SF
      
4
      
5
      
6
      
7
    
  

In [3]:

    

df_st = df1.stack()

df_st


    

    
Out[3]:





city  letters
LA    A          0
      B          1
      C          2
      D          3
SF    A          4
      B          5
      C          6
      D          7
dtype: int32

In [4]:

    

df_st.unstack()


    

    
Out[4]:






  

    

      
letters
      
A
      
B
      
C
      
D
    
    

      
city
      

      

      

      

    
  
  

    

      
LA
      
0
      
1
      
2
      
3
    
    

      
SF
      
4
      
5
      
6
      
7
    
  

In [6]:

    

df_st.unstack('letters')


    

    
Out[6]:






  

    

      
letters
      
A
      
B
      
C
      
D
    
    

      
city
      

      

      

      

    
  
  

    

      
LA
      
0
      
1
      
2
      
3
    
    

      
SF
      
4
      
5
      
6
      
7
    
  

In [7]:

    

df_st.unstack('city')


    

    
Out[7]:






  

    

      
city
      
LA
      
SF
    
    

      
letters
      

      

    
  
  

    

      
A
      
0
      
4
    
    

      
B
      
1
      
5
    
    

      
C
      
2
      
6
    
    

      
D
      
3
      
7
    
  

In [8]:

    

# how to stack/unstack handle null values
ser1 = Series([0,1,2],index=['Q','X','Y'])


    

In [9]:

    

ser2 = Series([4,5,6],index=['X','Y','Z'])


    

In [10]:

    

ser1


    

    
Out[10]:





Q    0
X    1
Y    2
dtype: int64

In [11]:

    

ser2


    

    
Out[11]:





X    4
Y    5
Z    6
dtype: int64

In [12]:

    

df = pd.concat([ser1,ser2], keys=['Alpha','Bravo'])

df


    

    
Out[12]:





Alpha  Q    0
       X    1
       Y    2
Bravo  X    4
       Y    5
       Z    6
dtype: int64

In [13]:

    

df.unstack()


    

    
Out[13]:






  

    

      

      
Q
      
X
      
Y
      
Z
    
  
  

    

      
Alpha
      
0.0
      
1.0
      
2.0
      
NaN
    
    

      
Bravo
      
NaN
      
4.0
      
5.0
      
6.0
    
  

In [15]:

    

# remove null values while stacking
df.unstack().stack()


    

    
Out[15]:





Alpha  Q    0.0
       X    1.0
       Y    2.0
Bravo  X    4.0
       Y    5.0
       Z    6.0
dtype: float64

In [16]:

    

# keep null values while stacking
df.unstack().stack(dropna=False)


    

    
Out[16]:





Alpha  Q    0.0
       X    1.0
       Y    2.0
       Z    NaN
Bravo  Q    NaN
       X    4.0
       Y    5.0
       Z    6.0
dtype: float64

In [ ]: