Pivoting on multiple columns causes data loss
Seen on HEAD. This problem is new since 0.5.0.

```
In [3]: data
Out[3]: 
   foo   bar   baz   spam   data
0  foo1  bar1  baz1  spam2  20  
1  foo1  bar2  baz1  spam3  30  
2  foo2  bar2  baz1  spam2  40  
3  foo1  bar1  baz2  spam1  50  
4  foo3  bar1  baz2  spam1  60  

In [4]: pandas.pivot_table(data, values="data", rows=["foo", "bar"], cols=["baz", "spam"])
Out[4]: 
  baz      baz1   baz2 
  spam     spam1  spam1
foo  bar               
foo1 bar1  20     50   
     bar2  30     NaN  
foo2 bar2  40     NaN  
foo3 bar1  NaN    60   
```

As you can see, the `("baz1", "spam2")`, `("baz2", "spam2")`, `("baz1", "spam3")` and `("baz2", "spam3")` columns have disappeared and their contents have been aggregated into the remaining two columns.
