title: Pandas read_csv not obeying a regex sep
body: <p><strong>Data</strong>:</p>
  
  <pre><code>from io import StringIO
  import pandas as pd
  
  s = '''ID,Level,QID,Text,ResponseID,responseText,date_key,last
  375280046,S,D3M,Which is your favorite?,D5M0,option 1,2012-08-08 00:00:00,ynot
  375280046,S,D3M,How often? (at home, at work, other),D3M0,Work,2010-03-31 00:00:00,okkk
  375280046,M,A78,Do you prefer a, b, or c?,A78C,a,2010-03-31 00:00:00,abc
  376918925,M,A78,Which ONE (select only one),A78E,Milk,2004-02-02 00:00:00,launch Wed., '''
  
  df = pd.read_csv(StringIO(s), sep=r',(?!\s)')
  </code></pre>
  
  <p><strong>Problem</strong>: I asked a question <a href="https://stackoverflow.com/questions/44786415/read-csv-with-extra-commas-and-no-quotechar-with-pandas">here</a>. I ran into a new problem though. Notice at the end of the last line, it's a comma and a space. The regex in <code>sep=r',(?!\s)'</code> is supposed to ignore commas that are followed by a space.</p>
  
  <p><strong>Question</strong>: Is there a way to read the last column as literally <code>launch Wed.,</code> where the comma isn't a separator/delimiter but is literally a comma in the <code>last</code> column text - using <code>pd.read_csv</code> only?</p>
  
  <p><strong>Error</strong>:</p>
  
  <pre><code>ValueError: Expected 8 fields in line 5, saw 9. Error could possibly be due to quotes being ignored when a multi-char delimiter is used.
  </code></pre>
  
  <p><strong>Expected / desired output</strong>:</p>
  
  <pre><code>          ID Level  QID                                  Text ResponseID  \
  0  375280046     S  D3M               Which is your favorite?       D5M0   
  1  375280046     S  D3M  How often? (at home, at work, other)       D3M0   
  2  375280046     M  A78             Do you prefer a, b, or c?       A78C   
  3  376918925     M  A78           Which ONE (select only one)       A78E   
  
    responseText             date_key           last  
  0     option 1  2012-08-08 00:00:00           ynot  
  1         Work  2010-03-31 00:00:00           okkk  
  2            a  2010-03-31 00:00:00            abc  
  3         Milk  2004-02-02 00:00:00  launch Wed.,   
  </code></pre>