pd.read_fwf removes leading and trailing whitespace
#### Code Sample, a copy-pastable example if possible

```python
from io import StringIO
import pandas as pd

data = u""" a bbb
 ccdd """

df = pd.read_fwf(StringIO(data), widths=[3, 3], header=None)
```

The output is
```python
>>> df.iloc[0,0]
u'a'
```

#### Expected Output
```python
u' a '
```

#### Problem description

Apparently, leading and trailing whitespaces are removed but I want to keep them. Adding dtype options, converters does not solve the problem. Is this expected behaviour?

I do not think this is intended because if we implement the same example with ``pd.read_csv()``, whitespaces are preserved.

```python
from io import StringIO
import pandas as pd

data = u""" a ,bbb
 cc,dd """

df = pd.read_csv(StringIO(data), header=None)
```
```python
>>> df.iloc[0, 0]
' a '
```

For consistency, behaviour should be identical.

The problem is also mentioned on Stackoverflow (https://stackoverflow.com/questions/41558138/pandas-read-fwf-removing-leading-and-trailing-whitespace). 

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 69 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
