title: ValueError: Unable to parse string "15,181.80" at position 0
body: <p>I am trying to convert a df to all numeric values but getting the following error.</p>
  <pre><code>ValueError: Unable to parse string &quot;15,181.80&quot; at position 0
  </code></pre>
  <p>Here is my current code:</p>
  <pre class="lang-html prettyprint-override"><code>data = pd.read_csv('pub?gid=1704010735&amp;single=true&amp;output=csv',
                   usecols=[0,1,2], 
                   header=0,
                   encoding=&quot;utf-8-sig&quot;,
                   index_col='Date') 
  
  data.apply(pd.to_numeric)
  
  print(&quot;we have a total of:&quot;, len(data), &quot; samples&quot;)
  
  data.head()
  </code></pre>
  
  <p>And df before I am trying to convert:</p>
  <p><div class="snippet" data-lang="js" data-hide="false" data-console="true" data-babel="false">
  <div class="snippet-code">
  <pre class="snippet-code-html lang-html prettyprint-override"><code>Clicks  Impressions
  Date        
  01/03/2020  15,181.80   1.22%
  02/03/2020  12,270.76   0.56%
  03/03/2020  39,420.79   0.80%
  04/03/2020  22,223.97   0.79%
  05/03/2020  17,084.45   0.88%</code></pre>
  </div>
  </div>
  </p>
  <p>I think the issue is that it handle the special characters E.G. &quot;,&quot; - is this correct? What is the best recommendation to help convert the DF into all numeric values?</p>
  <p>Thanks!</p>