BUG: Series Index 0 displays wrong data after converting String index to DatetimeIndex
After I convert the index from String to DatetimeIndex, index 0 seems to always point to the data near the Unix epoch. In the example below, b['Close'][0] correctly displays 4, but after the index conversion, b['Close'][0] now shows 54 (1/1/1970). Same goes with Open, High, Low, and Volume. Index other than 0 appears okay. If I use the slice notation, it would display the correct data. The to_csv also displays the right data.

```
>>> pd.__version__
'0.12.0'
>>> np.__version__
'1.7.1'

>>> b = pd.read_csv('/mnt/Investing/data-new/staging/b.csv', index_col=0)
>>> b['Close'][0]
4
>>> b
            Open  High  Low  Close  Volume
Date                                      
12/27/1969     1     2    3      4       5
12/28/1969    11    12   13     14      15
12/29/1969    21    22   23     24      25
12/30/1969    31    32   33     34      35
12/31/1969    41    42   43     44      45
1/1/1970      51    52   53     54      55
1/2/1970      61    62   63     64      65
1/3/1970      71    72   73     74      75
1/4/1970      81    82   83     84      85
1/5/1970      91    92   93     94      95
>>> b.index = pd.DatetimeIndex(b.index)
>>> b['Close'][0]
54
>>> b
            Open  High  Low  Close  Volume
1969-12-27     1     2    3      4       5
1969-12-28    11    12   13     14      15
1969-12-29    21    22   23     24      25
1969-12-30    31    32   33     34      35
1969-12-31    41    42   43     44      45
1970-01-01    51    52   53     54      55
1970-01-02    61    62   63     64      65
1970-01-03    71    72   73     74      75
1970-01-04    81    82   83     84      85
1970-01-05    91    92   93     94      95
>>> b['Close'][0:1]
1969-12-27    4
Name: Close, dtype: int64
>>> b['Close'][0:2]
1969-12-27     4
1969-12-28    14
Name: Close, dtype: int64


```
