ENH: Construct Panel from 2D structured array
Right now (0.18.1), I can construct a DataFrame from a "1D" structured array.  The NumPy structure field names are used as the Pandas column names.

But I cannot construct a Panel from a structured array:

```
arr = np.zeros((3,5), [('x',float), ('y',bool)])
pd.Panel(arr) # error
```

> ValueError: The number of dimensions required is 3, but the number of dimensions of the ndarray given was 2

One "obvious" way is slow:

```
pd.Panel(dict(enumerate(pd.DataFrame(a) for a in arr)))
```

And an efficient way is verbose:

```
dtyp = np.array(arr.dtype.names)
dim = arr.shape[0], arr.shape[1], dtyp.shape[0]
pd.Panel(pd.DataFrame(arr.ravel()).values.reshape(dim), minor_axis=dtyp)
```

Note that both of the above ways "promote" all values to a single dtype, which in my case (float + bool) becomes object.  That's really bad--I need to preserve the original dtypes so that if I do `panel[0].dtypes` matches `arr[0].dtype`.  I created #14512 for that problem.

Background for this issue is here: http://stackoverflow.com/questions/40259034/construct-pandas-panel-from-2d-structured-numpy-array

I'm using Pandas 0.18.1.
