title: Convert a HTML that doesn't contain a table to pandas Dataframe
body: <p>I have an HTML I want to read with pandas, the problem is the HTML is not a table, although, on the website it looks like one, I have it like this:</p>
  <pre><code>table = '''
  &lt;div id=&quot;companyResults&quot;&gt;
  &lt;div class=&quot;col-md-12 titles&quot;&gt;
  &lt;div class=&quot;col-md-6&quot;&gt; &lt;/div&gt;
  &lt;div class=&quot;col-md-4&quot;&gt;LOCATION&lt;/div&gt;
  &lt;div class=&quot;col-md-2 last&quot;&gt;SALES REVENUE ($M)&lt;/div&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-12 data&quot;&gt;
  &lt;div class=&quot;col-md-6&quot;&gt;
  &lt;a href=&quot;/business-directory/company-profiles.shenzhen_zhaoji_optical_co_ltd.bcf9d7eb4856eb739ec66272a6d9a361.html&quot;&gt;
                                          Shenzhen Zhaoji Optical Co., Ltd.&lt;/a&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-4&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Country:&lt;/div&gt;
                                  Shenzhen,
                                  Guangdong,
                                  &lt;br/&gt;
                                  China&lt;/div&gt;
  &lt;div class=&quot;col-md-2 last&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Sales Revenue ($M):&lt;/div&gt;
  &lt;/div&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-12 data&quot;&gt;
  &lt;div class=&quot;col-md-6&quot;&gt;
  &lt;a href=&quot;/business-directory/company-profiles.foxconn_industrial_internet_co_ltd.0d4c40a311dbfb1169684a21caa8794c.html&quot;&gt;
                                          Foxconn Industrial Internet Co., Ltd.&lt;/a&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-4&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Country:&lt;/div&gt;
                                  Shenzhen,
                                  Guangdong,
                                  &lt;br/&gt;
                                  China&lt;/div&gt;
  &lt;div class=&quot;col-md-2 last&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Sales Revenue ($M):&lt;/div&gt;
                                  $40,833.44M&lt;/div&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-12 data&quot;&gt;
  &lt;div class=&quot;col-md-6&quot;&gt;
  &lt;a href=&quot;/business-directory/company-profiles.boe_technology_group_co_ltd.61b87aa6bc863b69d8d7689703a3ac52.html&quot;&gt;
                                          BOE Technology Group Co., Ltd.&lt;/a&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-4&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Country:&lt;/div&gt;
                                  Beijing,
                                  Beijing,
                                  &lt;br/&gt;
                                  China&lt;/div&gt;
  &lt;div class=&quot;col-md-2 last&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Sales Revenue ($M):&lt;/div&gt;
                                  $16,495.55M&lt;/div&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-12 data&quot;&gt;
  &lt;div class=&quot;col-md-6&quot;&gt;
  &lt;a href=&quot;/business-directory/company-profiles.futong_group_co_ltd.85c12cb0d89005d1280cd3c0c13879ff.html&quot;&gt;
                                          Futong Group Co., Ltd.&lt;/a&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-4&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Country:&lt;/div&gt;
                                  Hangzhou,
                                  Zhejiang,
                                  &lt;br/&gt;
                                  China&lt;/div&gt;
  &lt;div class=&quot;col-md-2 last&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Sales Revenue ($M):&lt;/div&gt;
  &lt;/div&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-12 data&quot;&gt;
  &lt;div class=&quot;col-md-6&quot;&gt;
  &lt;a href=&quot;/business-directory/company-profiles.ofilm_group_co_ltd.515f10b35d850547d16fb6d6875a57d9.html&quot;&gt;
                                          OFILM Group Co., Ltd.&lt;/a&gt;
  &lt;/div&gt;
  &lt;div class=&quot;col-md-4&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Country:&lt;/div&gt;
                                  Shenzhen,
                                  Guangdong,
                                  &lt;br/&gt;
                                  China&lt;/div&gt;
  &lt;div class=&quot;col-md-2 last&quot;&gt;
  &lt;div class=&quot;show-mobile&quot;&gt;Sales Revenue ($M):&lt;/div&gt;
                                  $5,355.25M&lt;/div&gt;
  &lt;/div&gt;
  '''
  </code></pre>
  <p>I want an output that looks like this:</p>
  <pre><code>                                                            LOCATION  \
  0      Shenzhen Zhaoji Optical Co., Ltd.  Shenzhen, Guangdong, China   
  1  Foxconn Industrial Internet Co., Ltd.  Shenzhen, Guangdong, China   
  2         BOE Technology Group Co., Ltd.     Beijing, Beijing, China   
  3                 Futong Group Co., Ltd.   Hangzhou, Zhejiang, China   
  4                  OFILM Group Co., Ltd.  Shenzhen, Guangdong, China   
  
    SALES REVENUE ($M)  
  0                     
  1        $40,833.44M  
  2        $16,495.55M  
  3                     
  4         $5,355.25M  
  </code></pre>
  <p>I tried:</p>
  <pre><code>pd.read_html(str(table))
  </code></pre>
  <p>but got this:</p>
  <pre><code>ValueError: No tables found
  </code></pre>
  <p>So what is the best way possible to achieve that?
  PS: any more details added to rows (like href or whatever) is recommended but not a must</p>
  <p>Update: The <a href="https://www.dnb.com/business-directory/company-information.semiconductorelectronic-component-manufacturing.cn.html?page=1" rel="nofollow noreferrer">url</a></p>