Make DataFrame.pivot index argument truly optional

[lodagro]

Creating a pivot table from a DataFrame is easy.

In [17]: df
Out[17]: 
                 date variable     value
0 2000-01-03 00:00:00        A  0.528219
1 2000-01-04 00:00:00        A -0.135071
2 2000-01-05 00:00:00        A -0.343018
3 2000-01-03 00:00:00        B -0.097701
4 2000-01-04 00:00:00        B -1.383248

In [18]: df.pivot('date', 'variable', 'value')
Out[18]: 
variable           A         B
date                          
2000-01-03  0.528219 -0.097701
2000-01-04 -0.135071 -1.383248
2000-01-05 -0.343018       NaN

However if the index has been set, and there is no column to be set as index, pivot fails. From api point of view, the index argument is optional, but in fact it is not.

In [19]: df.set_index('date', inplace=True)

In [20]: df
Out[20]: 
           variable     value
date                         
2000-01-03        A  0.528219
2000-01-04        A -0.135071
2000-01-05        A -0.343018
2000-01-03        B -0.097701
2000-01-04        B -1.383248

In [21]: df.pivot(columns='variable', values='value')
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
...
KeyError: u'no item named None'

Of course one can reset the index before using pivot.

In [22]: df.reset_index().pivot('date', 'variable', 'value')
Out[22]: 
variable           A         B
date                          
2000-01-03  0.528219 -0.097701
2000-01-04 -0.135071 -1.383248
2000-01-05 -0.343018       NaN