title: How to scrape tr's with different column tags (1 = td and 2 = a within td)?
body: <p>I have a problem scraping a table. The table consist of the following rows, please refer to the html code below:</p>
  
  <pre><code>&lt;tr&gt;
      &lt;td align="center" class="hell" width="20%"&gt; &lt;b&gt;1 : 0&lt;/b&gt; &lt;/td&gt;
      &lt;td class="hell"&gt; &lt;a href="/speler_profiel/tjeerd-westdijk/" title="Tjeerd Westdijk"&gt;Tjeerd Westdijk&lt;/a&gt; 1.&lt;/td&gt;
  &lt;/tr&gt;, 
  &lt;tr&gt;
      &lt;td align="center" class="dunkel" width="20%"&gt;&lt;b&gt;2 : 0&lt;/b&gt;&lt;/td&gt;
      &lt;td class="dunkel"&gt;&lt;a href="/speler_profiel/emiel-wendt/" title="Emiel Wendt"&gt;Emiel Wendt&lt;/a&gt; 20.&lt;/td&gt;
  &lt;/tr&gt;
  </code></pre>
  
  <p>Please note that each row consist of two columns. From the first column (td) I just want to scrape the text within the  tags so-> '1 : 0' &amp; '2 : 0 '. From the second column I only want to scrape the text within the a tags so-> 'Tjeerd Westdijk' &amp; 'Emiel Wendt'.</p>
  
  <p>When I run my code (please refer to below) I get the text outside of the a tags (in the second column as  well) i.e. 1. &amp; 20.</p>
  
  <p>This is my code:</p>
  
  <pre><code>scores = []
  
  for row in td1_7[start:end]:
  scores.append([data.get_text(strip=True) for data in row.find_all('td')])
  
  final_df = pd.DataFrame(scores, columns=['Score','Playes'])
  
  print(final_df)
  </code></pre>
  
  <p>this gives me the following output:</p>
  
  <p>Score                           Playes
  0  1 : 0                Tjeerd Westdijk1.
  1  2 : 0                   Emiel Wendt20.</p>
  
  <p>How can I remove the 1 and 20. in the column players?</p>