Read CSV error_bad_lines does not error for too many values in first data row
Hi, I would like to report an unexpected behaviour connected with option error_bad_lines (I just reference this for make it easier to find this bug if someone was to report the same).

Given the following two CSV files:
simple.csv

```
Col1,Col2
4,Here
5,7,Invalid
8,Row
9,Does
10,Break
```

simple2.csv

```
Col1,Col2
5,7,Invalid
4,Row
8,Does
9,Not
10,Break
```

The following code breaks, as expected:

```
df = pd.read_csv('simple.csv')
```

The fact that the following code does not break is up to discussion (though it is inconsistent depending on whether an error is in first row or futher ones):

```
df2 = pd.read_csv('simple2.csv')
```

As the index is read as the first column and hence it comes down to another potential issue reported (ragarding erroring on too few values), so I am not going into this here.

So the result is as follows:

```
    Col1        Col2
5   7       Invalid
4   Row     NaN
8   Does    NaN
9   Not     NaN
10  Break   NaN
```

However even if I specify explicitly, that there is no index in CSV:

```
df3 = pd.read_csv('simple2.csv', index_col=False)
```

It still works, yielding the result:

```
    Col1    Col2
0   5       7
1   4       Row
2   8       Does
3   9       Not
4   10      Break
```

And this is definitely a bug I believe. I discovered it by accident, as in CSV that I was about to read comma was used also as decimal separator in first column and the totally corrupted CSV ended up read and parsed as DataFrame.
#### output of `pd.show_versions()`
## INSTALLED VERSIONS

commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.17.1
nose: 1.3.7
pip: 8.0.3
setuptools: 20.1.1
Cython: 0.23.4
numpy: 1.10.1
scipy: 0.16.0
statsmodels: 0.6.1
IPython: 4.0.1
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.4.2
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.4
matplotlib: 1.5.0
openpyxl: 2.2.6
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.7.7
lxml: 3.4.4
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.9
pymysql: None
psycopg2: None
Jinja2: 2.8
