PERF: speed up multi-key groupby
Improves multi-key `groupby` speed; On master:

```
In [3]: pd.__version__
Out[3]: '0.14.1-276-g995f91c'

In [4]: np.random.seed(2718281)

In [5]: n = 20000

In [6]: df = pd.DataFrame(np.random.randint(1, n, (n, 3)),
   ...:         columns=['jim', 'joe', 'jolie'])

In [7]: %timeit df.groupby(['jim', 'joe'])['jolie'].transform('max')
1 loops, best of 3: 1.09 s per loop

In [8]: df['joe'] = df['jim']

In [9]: %timeit df.groupby(['jim', 'joe'])['jolie'].transform('max')
1 loops, best of 3: 1.02 s per loop
```

note that it is not responsive to the reduction in number of groups. With this patch:

```
In [9]: %timeit df.groupby(['jim', 'joe'])['jolie'].transform('max')
10 loops, best of 3: 122 ms per loop

In [10]: df['joe'] = df['jim']

In [11]: %timeit df.groupby(['jim', 'joe'])['jolie'].transform('max')
10 loops, best of 3: 82.3 ms per loop
```

benching:

```
-------------------------------------------------------------------------------
Test name                                    | head[ms] | base[ms] |  ratio   |
-------------------------------------------------------------------------------
groupby_transform_multi_key2                 |  48.2820 | 810.2150 |   0.0596 |
groupby_transform_multi_key4                 | 137.5050 | 1986.8030 |   0.0692 |
groupby_transform_multi_key1                 |  70.1749 | 841.8140 |   0.0834 |
groupby_transform_multi_key3                 | 713.8393 | 2613.6247 |   0.2731 |
-------------------------------------------------------------------------------
Test name                                    | head[ms] | base[ms] |  ratio   |
-------------------------------------------------------------------------------

Ratio < 1.0 means the target commit is faster then the baseline.
Seed used: 1234

Target [11cc057] : Merge branch 'groupby-speed-up' of https://github.com/behzadnouri/pandas into behzadnouri-groupby-speed-up
Base   [3bb0803] : Merge pull request #8103 from sinhrks/pivot_dt

BUG: pivot_table raises KeyError with nameless index and columns
```
