read_csv Conflict between "thousands = ','" and "header = None"
#### Code Sample, a copy-pastable example if possible

```python
In [3]: pd.read_csv( 'test_data_with_commas.csv', header = None).head()
Out[3]:
            0                 1
0   area_code  indicator_test_1
1      area_1             1,000
2      area_2             2,000
3      area_3             3,000
4      area_4            54,908


In [4]: pd.read_csv( 'test_data_with_commas.csv', header = None, thousands=',')
Out[4]:
            0                 1
0   area_code  indicator_test_1
1      area_1             1,000
2      area_2             2,000
3      area_3             3,000
4      area_4            54,908


In [5]: pd.read_csv( 'test_data_with_commas.csv', header = 1, thousands=',').head()
Out[5]:
     area_1   1,000
0    area_2    2000
1    area_3    3000
2    area_4   54908
3    area_5   56932
4    area_6   73000

```
#### Problem description

When reading csv data using read_csv, if the header argument is set to 'None' specifying a string thousands separator does not remove this separator from the data.

Integer inputs for the header argument do not affect the removal of thousand separators.

I would expect the thousand separator to be removed from the data regardless of the value of the headers argument.

#### Expected Output
```python
In [3]: pd.read_csv( 'test_data_with_commas.csv', header = None).head()
Out[3]:
            0                 1
0   area_code  indicator_test_1
1      area_1             1,000
2      area_2             2,000
3      area_3             3,000
4      area_4            54,908


In [4]: pd.read_csv( 'test_data_with_commas.csv', header = None, thousands=',')
Out[4]:
            0                 1
0   area_code  indicator_test_1
1      area_1             1000
2      area_2             2000
3      area_3             3000
4      area_4            54908


In [5]: pd.read_csv( 'test_data_with_commas.csv', header = 1, thousands=',').head()
Out[5]:
     area_1   1,000
0    area_2    2000
1    area_3    3000
2    area_4   54908
3    area_5   56932
4    area_6   73000
```
#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Windows
OS-release: 8.1
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.3
pytest: 2.9.2
pip: 9.0.3
setuptools: 23.0.0
Cython: 0.24
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 4.2.0
sphinx: 1.4.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2018.5
blosc: None
bottleneck: 1.1.0
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: 4.5.1
html5lib: 0.999999999
sqlalchemy: 1.0.13
pymysql: None
psycopg2: 2.7.3.1 (dt dec pq3 ext lo64)
jinja2: 2.8
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
