bug? with `delim_whitespace` and 'skiprows' in `read_csv`
Hi all,

I've updated to version 0.15.1 from 0.14.x (Python3.4) and the following code fails in the latest version if the blank line (third line) in `data` has a tab or whitespace (I think it should be ignored when `skiprows` is used):

``` Python
import io

import pandas as pd

data = """Lat=0  Lon=0
Whatever - Not very important

YYYYMMDD HHMM  M(m/s) D(deg)  T(C)  De(k/m3) PRE(hPa)      RiNumber  RH(%)
19840101 0000   21.7    237    9.1    1.23     996.3           0.09   87.4
19840101 0100   22.4    239    9.4    1.23     995.7           0.10   87.2
19840101 0200   22.5    240    9.5    1.23     995.2           0.11   87.5"""

pd.read_csv(io.StringIO(data), delim_whitespace = True, skiprows = 4)
```

The output with a whitespace or tab in the third line (blank line part of the header) is:

<table>
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>YYYYMMDD</th>
      <th>HHMM</th>
      <th>M(m/s)</th>
      <th>D(deg)</th>
      <th>T(C)</th>
      <th>De(k/m3)</th>
      <th>PRE(hPa)</th>
      <th>RiNumber</th>
      <th>RH(%)</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td> 19840101</td>
      <td>   0</td>
      <td> 21.7</td>
      <td> 237</td>
      <td> 9.1</td>
      <td> 1.23</td>
      <td> 996.3</td>
      <td> 0.09</td>
      <td> 87.4</td>
    </tr>
    <tr>
      <th>1</th>
      <td> 19840101</td>
      <td> 100</td>
      <td> 22.4</td>
      <td> 239</td>
      <td> 9.4</td>
      <td> 1.23</td>
      <td> 995.7</td>
      <td> 0.10</td>
      <td> 87.2</td>
    </tr>
    <tr>
      <th>2</th>
      <td> 19840101</td>
      <td> 200</td>
      <td> 22.5</td>
      <td> 240</td>
      <td> 9.5</td>
      <td> 1.23</td>
      <td> 995.2</td>
      <td> 0.11</td>
      <td> 87.5</td>
    </tr>
  </tbody>
</table>


And the output without the whitespace and/or a tab is the expected:

<table>

  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>19840101</th>
      <th>0000</th>
      <th>21.7</th>
      <th>237</th>
      <th>9.1</th>
      <th>1.23</th>
      <th>996.3</th>
      <th>0.09</th>
      <th>87.4</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td> 19840101</td>
      <td> 100</td>
      <td> 22.4</td>
      <td> 239</td>
      <td> 9.4</td>
      <td> 1.23</td>
      <td> 995.7</td>
      <td> 0.10</td>
      <td> 87.2</td>
    </tr>
    <tr>
      <th>1</th>
      <td> 19840101</td>
      <td> 200</td>
      <td> 22.5</td>
      <td> 240</td>
      <td> 9.5</td>
      <td> 1.23</td>
      <td> 995.2</td>
      <td> 0.11</td>
      <td> 87.5</td>
    </tr>
  </tbody>
</table>


`pd.show_versions()` provides the following output:

```
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.1.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: x86
processor: x86 Family 6 Model 37 Stepping 5, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.15.1
nose: 1.3.4
Cython: None
numpy: 1.9.1
scipy: 0.14.0
statsmodels: 0.6.0
IPython: 3.0.0-dev
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.1
pytz: 2014.9
bottleneck: None
tables: None
numexpr: None
matplotlib: 1.4.0
openpyxl: None
xlrd: 0.9.3
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
rpy2: 2.4.4
sqlalchemy: 0.9.8
pymysql: None
psycopg2: None
```
