Segfault with array view and "large" dtypes
#### Code Sample

```python
import numpy as np
import pandas as p
import pathlib as pl
import struct as st

my_type = np.dtype([('1', '<u4'),
                 ('3',
                  [('4',
                    [('5', '<u4', (1000,))])])])

def convertArray(arr):
    return arr[4004:].view(my_type)

def loadArray(path):
    f = open(path, mode='rb')
    array = np.fromfile(f, dtype='uint8')
    my_data = convertArray(array)
    return my_data

def arrayToSeries(arr):
    part_of_arr = arr['3']
    return p.DataFrame(part_of_arr)

path = pl.Path('test_file')

frame = arrayToSeries(loadArray(path))

print(frame.head())

```
#### Problem description

The python interpreter segfaults.

How to generate the `test_file` (on linux):

`dd if=/dev/zero of=test_file bs=4004 count=1001`


#### Expected Output

The head of the DataFrame created from the file.
Or at least not a segfault, but a useful error message.

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.12-1-ARCH
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: de_AT.UTF-8
LOCALE: de_AT.UTF-8

pandas: 0.21.0
pytest: None
pip: 9.0.1
setuptools: 28.8.0
Cython: 0.27.3
numpy: 1.13.3
scipy: None
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.9
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0b10
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>

Edit: I now have tested with the newest master (54f2a5e91e90e35f7cbd15214297169831d6a6a6). Same result.

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.12-1-ARCH
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: de_AT.UTF-8
LOCALE: de_AT.UTF-8

pandas: 0.22.0.dev0+140.g54f2a5e91
pytest: None
pip: 9.0.1
setuptools: 28.8.0
Cython: 0.27.3
numpy: 1.13.3
scipy: None
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.9
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0b10
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
