API: consistency with .ix and .loc for getitem operations (GH8613)
closes #8613 

```
In [1]:      df = DataFrame(np.random.randn(5,4), columns=list('ABCD'), index=date_range('20130101',periods=5))

In [2]:      df
Out[2]: 
                   A         B         C         D
2013-01-01 -1.380065  1.221596  0.279703 -0.119258
2013-01-02  1.684202 -0.202251 -0.961145 -1.595015
2013-01-03 -0.623634 -2.377577 -3.024554 -0.298809
2013-01-04 -1.251699  0.456356  1.257002  1.465878
2013-01-05  0.687818 -2.125079  1.454911  1.914207

In [5]:      s = Series(range(5),[-2,-1,1,2,3])

In [6]:      s
Out[6]: 
-2    0
-1    1
 1    2
 2    3
 3    4
dtype: int64

In [7]:      df.loc['2013-01-02':'2013-01-10']
Out[7]: 
                   A         B         C         D
2013-01-02  1.684202 -0.202251 -0.961145 -1.595015
2013-01-03 -0.623634 -2.377577 -3.024554 -0.298809
2013-01-04 -1.251699  0.456356  1.257002  1.465878
2013-01-05  0.687818 -2.125079  1.454911  1.914207

In [9]:      s.loc[-10:3]
Out[9]: 
-2    0
-1    1
 1    2
 2    3
 3    4
dtype: int64
```

```
# this used to be a KeyError
In [15]: df.loc[2:3]
TypeError: Cannot index datetime64 with <type 'int'> keys
```

Slicing with float indexers; now works for ix (loc worked before)

```
In [3]: s.loc[-1.0:2]
Out[3]: 
-1    1
 1    2
 2    3
dtype: int64

In [4]: s.ix[-1.0:2]
Out[4]: 
-1    1
 1    2
 2    3
dtype: int64

# [] raises
In [5]: s[-1.0:2]
TypeError: cannot do slice start value indexing on <class 'pandas.core.index.Int64Index'> with these indexers [-1.0] of <type 'float'>
```
