title: All of columnar values of Pandas dataframe in first column, how to extract to correct columns
body: <p>I am dealing with a messy csv with several columns. Some of the rows have all of the column values in the first column, like so:</p>
  <pre><code>
      City Edition Sport Discipline Athlete   NOC Gender  Event Event_gender  Medal
  330 Paris,1900,Cricket,Cricket,&quot;ROQUES, F.&quot;,FRA,Men,cricket,M,Silver    NaN NaN NaN NaN NaN NaN NaN NaN NaN
  331 Paris,1900,Cricket,Cricket,&quot;SCHNEIDAU, A.J.&quot;,FRA,Men,cricket,M,Silver   NaN NaN NaN NaN NaN NaN NaN NaN NaN
  332 Paris,1900,Cricket,Cricket,&quot;TERRY, Henry John&quot;,FRA,Men,cricket,M,Silver NaN NaN NaN NaN NaN NaN NaN NaN NaN
  333 Paris,1900,Cricket,Cricket,&quot;TOMALIN, P.H.&quot;,FRA,Men,cricket,M,Silver NaN NaN NaN NaN NaN NaN NaN NaN NaN
  334 Paris   1900.0  Croquet Croquet AUMOITTE    FRA Men double  M   Gold
  </code></pre>
  <p>The first four rows have all of the values under the <code>City</code> column, whereas the last row has the correct values across the respective columns. There are a few hundred thousand rows and almost all of them have the column issue. I have to keep all rows with the correct values as is.</p>
  <p><strong>EDIT</strong></p>
  <p>My csv_read is fine, the file itself is the problem. The rows that causing problems are inside quotation marks and the athlete names are inside quotes with an apostrophe separate last and first name. So I guess the best thing to do is to create a function to open the file that will strip the extra characters. Though this could be hard to pull off without using lots of memory, as there are 300k rows...</p>