BUG: Reduction methods cause transpose of Panel but not Panel4D
When you do apply a reduction operation on a Panel with axis > 0, it causes the returned panel to have its axes transposed compared to the original.  This is how it behaves in an example in the documentation, although I cannot find an explicit mention of it (if it isn't mentioned, perhaps it should be?).

However, this is not the case with Panel4D.  For all axis values, the input axis order and the output axis order are the same.  

This means code that works with reduction operations has to make a special case depending on the axis and the number of dimensions of the object.  

How to reproduce the issue:

Setup:

``` python
>>> import pandas as pd
>>> import numpy as np
>>> 
>>> arr4 = np.random.rand(5, 7, 11, 13)
>>> arr3 = arr4[:,:,:,0]
>>> 
>>> pan4 = pd.Panel4D(arr4)
>>> pan3 = pd.Panel(arr3)
```

This is all good:

``` python
>>> arr3.sum(0).shape == pan3.sum(0).shape
True
>>> arr4.sum(0).shape == pan4.sum(0).shape
True
>>> arr3.sum(0).shape
(7,11)
>>> pan3.sum(0).shape
(7,11)
>>> arr4.sum(0).shape
(7,11,13)
>>> pan4.sum(0).shape
(7,11,13)
```

Now try the same thing with axis=1:

``` python
>>> arr3.sum(1).shape == pan3.sum(1).shape
False
>>> arr4.sum(1).shape == pan4.sum(1).shape
True
>>> arr3.sum(1).shape
(5,11)
>>> pan3.sum(1).shape
(11,5)
>>> arr4.sum(1).shape
(5,11,13)
>>> pan4.sum(1).shape
(5,11,13)
```

And axis=2:

``` python
>>> arr3.sum(2).shape == pan3.sum(2).shape
False
>>> arr4.sum(2).shape == pan4.sum(2).shape
True
>>> arr3.sum(2).shape
(5,7)
>>> pan3.sum(2).shape
(7,5)
>>> arr4.sum(2).shape
(5,7,13)
>>> pan4.sum(2).shape
(5,7,13)
```

And axis=3 for Panel4D:

``` python
>>> arr4.sum(3).shape == pan4.sum(3).shape
True
>>> arr4.sum(3).shape
(5,7,11)
>>> pan4.sum(3).shape
(5,7,11)
```
