ENH: Add  a ```level``` option to ```pd.DataFrame.append()```
I have two dataframes:

The first one looks like this:

|       |          | variable |
|:----: |:------:   | :-----:|
| entry | subentry |          |
| 0  | 1       | X |
|    | 2       | Y |
|    | 3       | Z |

and the second one looks like:

|       |          | variable |
|:----: |:------:   | :-----:|
| entry | subentry |          |
| 0  | 1       | A |
|    | 2       | B |


I would like to merge the two dataframe such that I get:

|       |          | variable |
|:----: |:------:   | :-----:|
| entry | subentry |          |
| 0  | 1       | X |
|    | 2       | Y |
|    | 3       | Z |
| 1  | 1       | A |
|    | 2       | B |

Simply using ```df1.append(df2, ignore_index=True)``` gives 

|        |variable |
|:----:  |:-----:|
|     |         |
| 0   |X |
| 1   | Y |
| 2   | Z |
| 3   | A |
| 4   | B |

In other words, it appends on the highest level (level 1) in the dataframes. I think it important to allow the user dealing with mutli-index dataframes to specify which level of the dataframe to append on. In the simple example above, this would allow me to specify "entry" as the index to append on. 

 Here is a code sinppet that will reproduce the problem:

```
	arrays = [
	    np.array([0,0,0]),
	    np.array([0,1,2]),]
	arrays_2 = [
	    np.array([0,0]),
	    np.array([0,1]),]
	df1 = pd.DataFrame(np.random.randn(3, 1), index=arrays)
	df2 = pd.DataFrame(np.random.randn(2, 1), index=arrays_2)
	df = df1.append(df2, ignore_index=True)
	print(df)
```

 In practice, I am looking ao combine N dataframes, each with a different number of "entry" rows. So I am looking for an approach that will not rely on me knowing the exact  of the dataframes I am combining.