How to concatenate two Panels without duplicating Items axis (i.e. like columns in DataFrames)?
I am trying to concatenating two Panels with duplicate `Items` (but different `major_axes`) together, without actually having to duplicate items... Did some searching but couldn't find much on SO.

Unfortunately I cannot upload pics to github at the moment.. **But screens are attached [here](http://stackoverflow.com/questions/34652835/pandas-how-to-concatenate-two-panels-without-duplicating-items-axis-i-e-colum).**

To illustrate what I mean:

```
# create data
import pandas as pd
df1 = pd.DataFrame({'A' : [1, 2, 3], 'B' : [2, 5, 6]}, index={0, 1, 2})
df2 = pd.DataFrame({'A' : [1, 2, 3], 'B' : [2, 5, 6]}, index={3, 4, 5})
df3 = pd.DataFrame({'A' : [5, 2, 3], 'B' : [2, 5, 6]}, index={6, 7, 8})
df4 = pd.DataFrame({'A' : [6, 2, 3], 'B' : [2, 5, 6]}, index={9, 10, 11})

pan1 = pd.Panel({'X' : df1, 'Y': df2})
pan2 = pd.Panel({'X' : df3, 'Y': df4})

# concat these two panels above
pan3 = pd.concat([pan1, pan2])

pan3
Output:
<class 'pandas.core.panel.Panel'>
Dimensions: 4 (items) x 12 (major_axis) x 2 (minor_axis)
Items axis: X to Y
Major_axis axis: 0 to 11
Minor_axis axis: A to B
```

**Note that the `Items` axis for `pan3` is of length 4, while `pan1` and `pan2` both have `Items` axis of length 2.**

Looking at `pan3`'s `minor_axis`, I get duplicated columns in the frame below.  **This is my problem.**:

```
pan3.loc[:, :, 'B']
```

Screenshot: See this [link on SO](http://stackoverflow.com/questions/34652835/pandas-how-to-concatenate-two-panels-without-duplicating-items-axis-i-e-colum)

**What I actually want to see** can be replicated as follows in a more complicated way... (Not more duplicated columns in the screenshot):

```
df5 = pd.concat([df1, df3])
df6 = pd.concat([df2, df4])
pan4 = pd.Panel({'X':df5, 'Y':df6})
pan4.loc[:, :, 'B']
```

Screenshot: See this [link on SO](http://stackoverflow.com/questions/34652835/pandas-how-to-concatenate-two-panels-without-duplicating-items-axis-i-e-colum)

**Is this something that can be done with `pd.concat`?** Thanks guys.
