df[0:1] row select fails with Float64Index on 0.13.0
In pandas 0.12.0 and below I was always able to get at the first row of any data frame (returned as a wide one row DataFrame, not a series) by using df[0:1], regardless if my index was a float or int or something else.

Currently in 0.13.0 trying df[0:1] on a dataframe with a Float64Index fails.

Is there a better way in 0.13.0 to return the i-th row of a data frame as a wide one-row data frame?

currently df2.iloc[0,:] returns a series cross section which I dont want.

Thanks!

``` python
In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: df = pd.DataFrame(np.random.randn(10,10))

In [4]: df.index = df.index*100+3

In [5]: df
Out[5]:
            0         1         2         3         4         5         6  \
3    0.961295  0.150850 -1.357989 -1.981159  1.409971  1.165354  0.412334
103 -0.357906  0.861821 -0.911108  0.551928  1.402282 -0.409175  0.833893
203 -0.892805  0.312257 -0.829338 -0.290734  0.065603 -0.159384  1.160495
303  0.155798 -0.385063 -0.689650 -0.197156 -1.107738 -1.112956 -1.856549
403 -1.223597  0.039183 -1.810251  1.234489  0.446190  0.029870 -1.586065
503  0.113397  0.982866 -1.984421  0.574137  0.704638 -1.593602  0.815498
603  1.154750 -0.018192 -1.806763  0.746731 -0.181660 -0.608605  0.327122
703  1.536969  2.054841  0.168666 -0.996030 -0.238698 -0.415467  0.560634
803  1.083026  1.624360  0.836893  0.593568  0.328877 -0.000506  0.185452
903  0.239799 -0.552065  0.745946 -0.544161 -1.241497  0.771948 -0.709924

            7         8         9
3   -0.766668 -0.089740  0.731273
103  2.599487 -0.612015 -0.410110
203  0.737393 -1.406171 -1.676148
303 -0.574330 -0.031489 -0.991040
403 -0.366256 -0.853061 -0.093385
503  2.383536 -0.188622  0.030401
603 -1.463239  2.020704 -0.840727
703 -0.316375 -0.703592  1.359039
803 -2.133368  1.771383 -0.447949
903 -1.599941 -2.384423  0.178400

[10 rows x 10 columns]

In [6]: df[0:1]
Out[6]:
          0        1         2         3         4         5         6  \
3  0.961295  0.15085 -1.357989 -1.981159  1.409971  1.165354  0.412334

          7        8         9
3 -0.766668 -0.08974  0.731273

[1 rows x 10 columns]

In [7]: df2 = df.set_index(0)

In [8]: df2
Out[8]:
                  1         2         3         4         5         6  \
0
 0.961295  0.150850 -1.357989 -1.981159  1.409971  1.165354  0.412334
-0.357906  0.861821 -0.911108  0.551928  1.402282 -0.409175  0.833893
-0.892805  0.312257 -0.829338 -0.290734  0.065603 -0.159384  1.160495
 0.155798 -0.385063 -0.689650 -0.197156 -1.107738 -1.112956 -1.856549
-1.223597  0.039183 -1.810251  1.234489  0.446190  0.029870 -1.586065
 0.113397  0.982866 -1.984421  0.574137  0.704638 -1.593602  0.815498
 1.154750 -0.018192 -1.806763  0.746731 -0.181660 -0.608605  0.327122
 1.536969  2.054841  0.168666 -0.996030 -0.238698 -0.415467  0.560634
 1.083026  1.624360  0.836893  0.593568  0.328877 -0.000506  0.185452
 0.239799 -0.552065  0.745946 -0.544161 -1.241497  0.771948 -0.709924

                  7         8         9
0
 0.961295 -0.766668 -0.089740  0.731273
-0.357906  2.599487 -0.612015 -0.410110
-0.892805  0.737393 -1.406171 -1.676148
 0.155798 -0.574330 -0.031489 -0.991040
-1.223597 -0.366256 -0.853061 -0.093385
 0.113397  2.383536 -0.188622  0.030401
 1.154750 -1.463239  2.020704 -0.840727
 1.536969 -0.316375 -0.703592  1.359039
 1.083026 -2.133368  1.771383 -0.447949
 0.239799 -1.599941 -2.384423  0.178400

[10 rows x 9 columns]

In [9]: df2[0:1]
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-9-f015a308451a> in <module>()
----> 1 df2[0:1]

D:\Python27\lib\site-packages\pandas\core\frame.pyc in __getitem__(self, key)
   1621
   1622         # see if we can slice the rows
-> 1623         indexer = _convert_to_index_sliceable(self, key)
   1624         if indexer is not None:
   1625             return self._getitem_slice(indexer)

D:\Python27\lib\site-packages\pandas\core\indexing.pyc in _convert_to_index_sliceable(obj, key)
   1329     idx = obj.index
   1330     if isinstance(key, slice):
-> 1331         return idx._convert_slice_indexer(key, typ='getitem')
   1332
   1333     elif isinstance(key, compat.string_types):

D:\Python27\lib\site-packages\pandas\core\index.pyc in _convert_slice_indexer(self, key, typ)
   1809
   1810         # translate to locations
-> 1811         return self.slice_indexer(key.start, key.stop, key.step)
   1812
   1813     def get_value(self, series, key):

D:\Python27\lib\site-packages\pandas\core\index.pyc in slice_indexer(self, start, end, step)
   1491         This function assumes that the data is sorted, so use at your own peril
   1492         """
-> 1493         start_slice, end_slice = self.slice_locs(start, end)
   1494
   1495         # return a slice

D:\Python27\lib\site-packages\pandas\core\index.pyc in slice_locs(self, start, end)
   1530         else:
   1531             try:
-> 1532                 start_slice = self.get_loc(start)
   1533
   1534                 if not is_unique:

D:\Python27\lib\site-packages\pandas\core\index.pyc in get_loc(self, key)
   1015         loc : int if unique index, possibly slice or mask if not
   1016         """
-> 1017         return self._engine.get_loc(_values_from_object(key))
   1018
   1019     def get_value(self, series, key):

D:\Python27\lib\site-packages\pandas\index.pyd in pandas.index.IndexEngine.get_loc (pandas\index.c:3326)()

D:\Python27\lib\site-packages\pandas\index.pyd in pandas.index.IndexEngine.get_loc (pandas\index.c:3206)()

D:\Python27\lib\site-packages\pandas\hashtable.pyd in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:10591)()

D:\Python27\lib\site-packages\pandas\hashtable.pyd in pandas.hashtable.PyObjectHashTable.get_item (pandas\hashtable.c:10544)()

KeyError: 0
```
