BUG: not properly converting S1 in astype ,on PY3
I am trying to create a dataframe where each cell is represented as a single characters rather than python objects. I am able to create and work with the dataframe when using .astype command. However, If i try to print out a larger portion of the table, then I get an error.
#### Code Sample, a copy-pastable example if possible

```
import random
import pandas as pd
lets = 'ACDEFGHIJKLMNOP'
slen = 50
nseqs = 1000
words = [[random.choice(lets) for x in range(slen)] for _ in range(nseqs)]
df = pd.DataFrame(words).astype('S1')
#this will print correctly:
print(df.iloc[:60, :])
#this will raise an error:
print(df.iloc[:61, :])
```
#### error raised

```
C:\Anaconda3\lib\site-packages\pandas\core\internals.py in _vstack(to_stack, dtype)
   4248 
   4249     # work around NumPy 1.6 bug
-> 4250     if dtype == _NS_DTYPE or dtype == _TD_DTYPE:
   4251         new_values = np.vstack([x.view('i8') for x in to_stack])
   4252         return new_values.view(dtype)
TypeError: data type "bytes8" not understood
```
#### output of `pd.show_versions()`

commit: None
python: 3.4.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.17.1
nose: None
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
IPython: 4.1.1
sphinx: 1.4b1
patsy: 0.4.0
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.6
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.5.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.11
pymysql: None
psycopg2: None
Jinja2: 2.8
