title: Reading pipe-delimited file with html tags using Pandas into data-frame
body: <p>I've been reading a pipe-delimited data file in Mac with Pandas/Python. The data file contains chat transcripts without a header. The header info that we can give is <code>ID | Name | transcripts_text</code></p>
  <p>The sample text file is:</p>
  <p>P37001 | John | Thanks for reaching out. Our customer support agents <code>can&amp;rsquo;t</code>(can't) accept all applications or provide status through any of our contact channels, including phone and messaging.<code>&lt;br /&gt;</code></p>
  <p><code>&lt;br /&gt;</code></p>
  <p>You can use our <code>&lt;a href=&quot;https://www.google.com/&quot;&gt;</code> <code>&lt;span style=&quot;color: rgb(0, 0, 255);&quot;&gt;Payment Program&lt;/span&gt;&lt;/a&gt;</code> to apply for a loan. To check the status of your loan or for additional questions, please go to <code>the&amp;nbsp</code>;</p>
  <p><code>&lt;a href=&quot;https://google.com/&quot; target=&quot;_blank&quot;&gt;``&lt;span style=&quot;color: rgb(0, 0, 255);&quot;&gt;</code>Pay Program <code>&lt;/span&gt;&lt;/a&gt;.&lt;br /&gt; &amp;nbsp;</code>
  <code>&lt;p&gt;To apply for loan on your check Program loan, visit &lt;a href=&quot;http://google.com/&quot; ``target=&quot;_blank&quot;&gt;&lt;span style=&quot;color: rgb(0, 0, 255);&quot;&gt;google.com/&lt;/span&gt;&lt;/a&gt;.&lt;/p&gt;</code></p>
  <p><code>&lt;br /&gt;</code></p>
  <p><code>&lt;br /&gt;</code></p>
  <p><code>&amp;nbsp;</code></p>
  <p>P37002 | John | <code>&lt;span style=&quot;color: rgb(0, 0, 205);&quot;&gt;&lt;strong&gt;XX FORMAL MALE XX&lt;/strong&gt;&lt;/span&gt;&lt;br /&gt;</code></p>
  <p>To collect your personal information, a secure form will be available in the next few minutes within our conversation. When you see the message box change to the secure form, you can safely enter</p>
  <p><code>&amp;quot;Submit&amp;quot;</code>. After selecting &quot;Submit&quot; the message box will return and you can enter additional details of a non-personal nature into our conversation.<code>&lt;br /&gt;</code></p>
  <p><code>&lt;br /&gt;</code></p>
  <p><code>&lt;span style=&quot;color: rgb(0, 0, 205);&quot;&gt;&lt;strong&gt;XX FORMAL FEMALE XX&lt;/strong&gt;&lt;/span&gt;``&lt;br /&gt;</code>
  To collect your personal information, a secure webform will be available in the next few minutes within our conversation. When you see the message box change to the secure webform, you can safely enter your personal data and select <code>&amp;quot;Submit&amp;quot;</code>. After selecting <code>&amp;quot;Submit&amp;quot;</code> the message box will return and you can enter additional details of a non-personal nature into our conversation.</p>
  <p><code>&lt;br /&gt;</code></p>
  <p><code>&lt;br /&gt;</code></p>
  <p><code>&lt;br /&gt;</code></p>
  <p>Code:</p>
  <pre><code>import pandas as pd
  quick_reply=pd.read_csv('final.txt', names=['ID','Name','transcripts_text'], sep='|')
  </code></pre>
  <p>Output:</p>
  <pre><code>  ID     Name   transcripts_text
   P37001  John   Thanks for reaching out. Out..
   &lt;br /&gt;  NaN      NaN
  </code></pre>
  <p>Expected Output:</p>
  <pre><code>   ID     Name   transcripts_text
   P37001  John   Thanks for reaching out. Our customer support agents can't accept all applications or provide status through any of our contact channels, including phone and messaging.You can use our ..
  </code></pre>
  <p><code>Removing all the html tags. And the data is captured properly in pandas data frame considering P37001 data as single row and P37002 as second row</code></p>