title: Pandas won't separate columns in my comma separated .txt file
body: <p>I'm aware this has been asked so many times, but it's left me really scratching my head. I have a .txt file which looks like:</p>
  
  <p>"0,1,2,3,4, ....63,0,1,2,3,4.....63"</p>
  
  <p>"0,1,2,3,4, ....63,0,1,2,3,4.....63"</p>
  
  <p>"0,1,2,3,4, ....63,0,1,2,3,4.....63" </p>
  
  <p>and so on for multiple rows.
  So that's 64+64 = 128 columns separated by commas, while each row is enclosed in double quotes.</p>
  
  <p>I have used the commands:</p>
  
  <pre><code>#Used this initially
  df = pd.read_csv('test_data.txt')
  #Used this after reading more stackoverflow answers
  df = pd.read_csv('test_data.txt', header = None, sep=",", delimiter=',', quotechar='"', index_col = None)
  </code></pre>
  
  <p>I know sep and delimiter are the same parameters, but I tried both out anyway, I shouldn't have to specify these either because pandas chooses commas by default. 
  After this I'm just using:</p>
  
  <pre><code>df.head()
  </code></pre>
  
  <p>And it outputs:</p>
  
  <pre><code>                                                 0
  0   0.00,1.00,2.00,3.00,4.00,5.00,6.00,7.00,8.00,9...
  
  1   0.00,1.00,2.00,3.00,4.00,5.00,6.00,7.00,8.00,9...
  
  2   0.00,1.00,2.00,3.00,4.00,5.00,6.00,7.00,8.00,9...
  
  3   0.00,1.00,2.00,3.00,4.00,5.00,6.00,7.00,8.00,9...
  
  4   0.00,1.00,2.00,3.00,4.00,5.00,6.00,7.00,8.00,9...
  </code></pre>
  
  <p>It just reads it all as the one column, please advise on how I can read all 128 columns.</p>