In [1]:

    

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


    

In [2]:

    

import pandas.util.testing as tm
tm.N = 3


    

In [5]:

    

def unpivot(frame):
    N, K = frame.shape
    data = {'value': frame.values.ravel('F'), 
            'variable': np.asarray(frame.columns).repeat(N),
            'date': np.tile(np.asarray(frame.index), K)}
    
    return DataFrame(data, columns=['date', 'variable', 'value'])


    

In [6]:

    

dframe = unpivot(tm.makeTimeDataFrame())


    

In [7]:

    

dframe


    

    
Out[7]:






  

    

      

      
date
      
variable
      
value
    
  
  

    

      
0
      
2000-01-03
      
A
      
0.655934
    
    

      
1
      
2000-01-04
      
A
      
0.114627
    
    

      
2
      
2000-01-05
      
A
      
1.217039
    
    

      
3
      
2000-01-03
      
B
      
1.084729
    
    

      
4
      
2000-01-04
      
B
      
-2.776063
    
    

      
5
      
2000-01-05
      
B
      
0.097573
    
    

      
6
      
2000-01-03
      
C
      
0.811582
    
    

      
7
      
2000-01-04
      
C
      
0.078955
    
    

      
8
      
2000-01-05
      
C
      
-0.383991
    
    

      
9
      
2000-01-03
      
D
      
1.481837
    
    

      
10
      
2000-01-04
      
D
      
-1.139894
    
    

      
11
      
2000-01-05
      
D
      
0.104460
    
  

In [8]:

    

dframe_piv = dframe.pivot('date', 'variable', 'value')
dframe_piv


    

    
Out[8]:






  

    

      
variable
      
A
      
B
      
C
      
D
    
    

      
date
      

      

      

      

    
  
  

    

      
2000-01-03
      
0.655934
      
1.084729
      
0.811582
      
1.481837
    
    

      
2000-01-04
      
0.114627
      
-2.776063
      
0.078955
      
-1.139894
    
    

      
2000-01-05
      
1.217039
      
0.097573
      
-0.383991
      
0.104460
    
  

In [ ]: