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In [1]:

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



In [2]:

    
dframe1 = DataFrame(np.arange(8).reshape(2,4), index = pd.Index(['LA', 'SF'], name='city'), columns = pd.Index(list('ABCD'), name='letter'))



In [3]:

    
dframe_st = dframe1.stack()
dframe_st









    Out[3]:





city  letter
LA    A         0
      B         1
      C         2
      D         3
SF    A         4
      B         5
      C         6
      D         7
dtype: int64



In [4]:

    
dframe_st.unstack()



In [5]:

    
dframe_st.unstack('city')



In [6]:

    
ser1 = Series([0,1,2], index=list('QXY'))
ser2 = Series([4,5,6], index=list('XYZ'))



In [7]:

    
dframe = pd.concat([ser1, ser2], keys=['Alpha', 'Beta'])

dframe









    Out[7]:





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



In [8]:

    
dframe.unstack()



In [9]:

    
dframe.unstack().stack()









    Out[9]:





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



In [10]:

    
dframe.unstack().stack(dropna=False)









    Out[10]:





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



In [ ]: