API: select levels of a MultiIndex
Say you have a multi-index:

```
In [34]: idx = pd.MultiIndex.from_product([['a', 'b', 'c'], [1, 2, 3], ['f', 'g'
]], names=['lev0', 'lev1', 'lev2'])

In [35]: df = pd.DataFrame(range(len(idx)), index=idx)

In [36]: df
Out[36]:
                 0
lev0 lev1 lev2
a    1    f      0
          g      1
     2    f      2
          g      3
     3    f      4
          g      5
b    1    f      6
          g      7
     2    f      8
          g      9
     3    f     10
          g     11
c    1    f     12
          g     13
     2    f     14
          g     15
     3    f     16
          g     17
```

and you want to select certain levels of the Index (like you select columns of a frame, I want to select levels of an index and get a subset of the index).

At the moment, some possibilities:

```
In [37]: pd.MultiIndex.from_arrays([df.index.get_level_values(0), df.index.get_level_values(1)])
Out[37]:
MultiIndex(levels=[[u'a', u'b', u'c'], [1, 2, 3]],
           labels=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2], [0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2]],
           names=[u'lev0', u'lev1'])

In [38]: idx.droplevel(-1)    # if you know the ones to drop
Out[38]:
MultiIndex(levels=[[u'a', u'b', u'c'], [1, 2, 3]],
           labels=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2], [0, 0
, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2]],
           names=[u'lev0', u'lev1'])

In [39]: df.reset_index().set_index(['lev0','lev1']).index
Out[39]:
MultiIndex(levels=[[u'a', u'b', u'c'], [1, 2, 3]],
           labels=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2], [0, 0
, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2]],
           names=[u'lev0', u'lev1'])

In [40]: df.reset_index(-1).index       # if you know the ones to drop
Out[40]:
MultiIndex(levels=[[u'a', u'b', u'c'], [1, 2, 3]],
           labels=[[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2], [0, 0
, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2, 0, 0, 1, 1, 2, 2]],
           names=[u'lev0', u'lev1'])
```

Am I missing an easy way to do this?

And if not, I think we should have a better way to do this.

Note: triggerd by this SO question: http://stackoverflow.com/questions/31991388/combinations-of-multiindex-levels-which-occur-in-a-dataframe (but had already encountered this multiple times)
