read_csv, Error tokenizing data if initial whitespace in csv
Sample Dataset:
A,B,C,D,E,,F,G
H,I,J,K,L,,M,N
 ,O,P,Q,R,,S, 
T,U,V,W,X,,Y,Z

using the following read_csv:

```python
import pandas as pd
data= pd.read_csv("test_data.csv", sep=',', header=None, encoding='utf8')

```
gives following exception:

```
pandas.errors.ParserError: Error tokenizing data. C error: Buffer overflow caught - possible malformed input file.
```
If we use:
```
data= pd.read_csv("test_data.csv", sep=',', header=None, encoding='utf8', skip_blank_lines=False)
```
It works successfully, however we need skip_blank_lines active for additional purposes so this is not a viable workaround. 

It seems the issue is with the initial whitespace in the data set. If we strip out the initial whitespace, again it works successfully, but again, its not really a viable solution in large datasets that you have not control over. 

skipinitialspace seems like it would be a good use case here. However, since the whitespace is at start of row and not proceeded by a ',' delimiter. This will not work either.

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Darwin
OS-release: 18.0.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_IE.UTF-8
LOCALE: None.None

pandas: 0.23.4
pytest: 2.9.2
pip: 8.1.2
setuptools: 27.2.0
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.1
pyarrow: None
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
feather: None
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
