PERF: msgpack encoding changnes to use to/from string for speed boosts

API: disable sparse structure encodings and unicode indexes

```
-------------------------------------------------------------------------------
Test name                                    | head[ms] | base[ms] |  ratio   |
-------------------------------------------------------------------------------
packers_read_pack                            |   3.5113 |  17.8316 |   0.1969 |
packers_read_pickle                          |   0.6769 |   0.6770 |   0.9999 |
packers_write_pack                           |   1.8814 |   3.5230 |   0.5340 |
packers_write_pickle                         |   1.5387 |   1.4664 |   1.0493 |

packers_write_hdf_store                      |  12.1900 |  12.2033 |   0.9989 |
packers_read_csv                             |  52.3347 |  52.2310 |   1.0020 |
packers_write_csv                            | 536.2056 | 526.5187 |   1.0184 |
packers_write_hdf_table                      |  33.3436 |  32.4137 |   1.0287 |
packers_read_hdf_store                       |   8.3120 |   8.0493 |   1.0326 |
packers_read_hdf_table                       |  13.9607 |  12.9707 |   1.0763 |
-------------------------------------------------------------------------------
Test name                                    | head[ms] | base[ms] |  ratio   |
-------------------------------------------------------------------------------

Ratio < 1.0 means the target commit is faster then the baseline.
Seed used: 1234

Target [381e86b] : PERF: msgpack encoding changnes to use to/from string for speed boosts
API: disable sparse structure encodings and unicode indexes
Base   [46008ec] : DOC: add cookbook entry
```

A smaller frame
```
In [1]: df = DataFrame(np.random.rand(1000,100))

In [7]: %timeit -n 5 df.to_pickle('test.pickle')
5 loops, best of 3: 9.4 ms per loop

In [8]: %timeit -n 5 df.to_msgpack('test.pack')
5 loops, best of 3: 10.1 ms per loop
```

now pretty competitive with pickle