HDFStore does not conserve index correctly
I have DataFrame with DateRange index, and i store it with HDFStore to h5.

But when I retreive my DataFrame, there is a problem with the indices cause I get this error:
Exception: Index values are not unique

Here are the commands that produce the exception, I didn't test every possible case so I keep the commands in between that I executed:

dffc=pandas.DataFrame(vpp.forecast.data, index=dr_year_900[:-1])
dffc[start_dt:stop_dt]
dffc.ix[start_dt:stop_dt]
dffc.drop(['Counter'], axis=1)
dffc=dffc.drop(['Counter'], axis=1)
dffc.ix[start_dt:stop_dt]
dffc['EFor'] = dffc['Power'] - dffc['Forecast']
dffc.ix[start_dt:stop_dt]
dffc = dffc.rename(columns={'Power':'PRef', 'Forecast':'PFor'})
dffc
dffc.ix[start_dt:stop_dt]
dfs = pandas.HDFStore('test.h5', 'w')
dfs.put('dffc', dffc)
dfs.close()
del(dffc)
dfs = pandas.HDFStore('test.h5', 'r')
dffc
dffc = dfs['dffc']
dffc
dffc.ix[start_dt:stop_dt]
==> here is the output:
In [49]: dffc.ix[start_dt:stop_dt]
Out[49]: 
<class 'pandas.core.frame.DataFrame'>
DateRange: 961 entries, 2010-01-01 00:00:00 to 2010-01-11 00:00:00
offset: <900 Seconds>
Data columns:
Counter        961  non-null values
Forecast       961  non-null values
Imbalance      961  non-null values
NegImbPrice    961  non-null values
PosImbPrice    961  non-null values
Power          961  non-null values
Price          961  non-null values
dtypes: float64(6), object(1)

In [50]: dffc.drop(['Counter'], axis=1)
Out[50]: 
<class 'pandas.core.frame.DataFrame'>
DateRange: 35040 entries, 2010-01-01 00:00:00 to 2010-12-31 23:45:00
offset: <900 Seconds>
Data columns:
Forecast       35040  non-null values
Imbalance      35040  non-null values
NegImbPrice    35040  non-null values
PosImbPrice    35040  non-null values
Power          35040  non-null values
Price          35040  non-null values
dtypes: float64(6)

In [51]: dffc=dffc.drop(['Counter'], axis=1)

In [52]: dffc.ix[start_dt:stop_dt]
Out[52]: 
<class 'pandas.core.frame.DataFrame'>
DateRange: 961 entries, 2010-01-01 00:00:00 to 2010-01-11 00:00:00
offset: <900 Seconds>
Data columns:
Forecast       961  non-null values
Imbalance      961  non-null values
NegImbPrice    961  non-null values
PosImbPrice    961  non-null values
Power          961  non-null values
Price          961  non-null values
dtypes: float64(6)

In [53]: dffc['EFor'] = dffc['Power'] - dffc['Forecast']

In [54]: dffc.ix[start_dt:stop_dt]
Out[54]: 
<class 'pandas.core.frame.DataFrame'>
DateRange: 961 entries, 2010-01-01 00:00:00 to 2010-01-11 00:00:00
offset: <900 Seconds>
Data columns:
Forecast       961  non-null values
Imbalance      961  non-null values
NegImbPrice    961  non-null values
PosImbPrice    961  non-null values
Power          961  non-null values
Price          961  non-null values
EFor           961  non-null values
dtypes: float64(7)

In [55]: dffc = dffc.rename(columns={'Power':'PRef', 'Forecast':'PFor'})

In [56]: dffc
Out[56]: 
<class 'pandas.core.frame.DataFrame'>
DateRange: 35040 entries, 2010-01-01 00:00:00 to 2010-12-31 23:45:00
offset: <900 Seconds>
Data columns:
PFor           35040  non-null values
Imbalance      35040  non-null values
NegImbPrice    35040  non-null values
PosImbPrice    35040  non-null values
PRef           35040  non-null values
Price          35040  non-null values
EFor           35040  non-null values
dtypes: float64(7)

In [57]: dffc.ix[start_dt:stop_dt]
Out[57]: 
<class 'pandas.core.frame.DataFrame'>
DateRange: 961 entries, 2010-01-01 00:00:00 to 2010-01-11 00:00:00
offset: <900 Seconds>
Data columns:
PFor           961  non-null values
Imbalance      961  non-null values
NegImbPrice    961  non-null values
PosImbPrice    961  non-null values
PRef           961  non-null values
Price          961  non-null values
EFor           961  non-null values
dtypes: float64(7)

In [58]: dfs = pandas.HDFStore('test.h5', 'w')

In [59]: dfs.put('dffc', dffc)

In [60]: dfs.close()

In [61]: del(dffc)

In [62]: dfs = pandas.HDFStore('test.h5', 'r')
## In [63]: dffc

Traceback (most recent call last):
  File "<ipython console>", line 1, in <module>
NameError: name 'dffc' is not defined

In [64]: dffc = dfs['dffc']

In [65]: dffc
Out[65]: 
<class 'pandas.core.frame.DataFrame'>
Index: 35040 entries, 2010-01-01 00:00:00 to 2010-12-31 23:45:00
Data columns:
PFor           35040  non-null values
Imbalance      35040  non-null values
NegImbPrice    35040  non-null values
PosImbPrice    35040  non-null values
PRef           35040  non-null values
Price          35040  non-null values
EFor           35040  non-null values
dtypes: float64(7)
## In [66]: dffc.ix[start_dt:stop_dt]

Traceback (most recent call last):
  File "<ipython console>", line 1, in <module>
  File "C:\Python27\lib\site-packages\pandas-0.7.1-py2.7-win32.egg\pandas\core\indexing.py", line 35, in **getitem**
    return self._getitem_axis(key, axis=0)
  File "C:\Python27\lib\site-packages\pandas-0.7.1-py2.7-win32.egg\pandas\core\indexing.py", line 167, in _getitem_axis
    return self._get_slice_axis(key, axis=axis)
  File "C:\Python27\lib\site-packages\pandas-0.7.1-py2.7-win32.egg\pandas\core\indexing.py", line 345, in _get_slice_axis
    i, j = labels.slice_locs(start, stop)
  File "C:\Python27\lib\site-packages\pandas-0.7.1-py2.7-win32.egg\pandas\core\index.py", line 819, in slice_locs
    beg_slice = self.get_loc(start)
  File "C:\Python27\lib\site-packages\pandas-0.7.1-py2.7-win32.egg\pandas\core\index.py", line 499, in get_loc
    return self._engine.get_loc(key)
  File "engines.pyx", line 101, in pandas._engines.DictIndexEngine.get_loc (pandas\src\engines.c:2498)
  File "engines.pyx", line 107, in pandas._engines.DictIndexEngine.get_loc (pandas\src\engines.c:2447)
Exception: Index values are not unique

How can I avoid this problem?
