title: Find the similar texts across the python dataframe
body: <p>Suppose I have a python dataframe as follows,</p>
  
  <pre><code>data['text']
  
  abc.google.com
  d-2667808233512566908.ampproject.net
  d-27973032622323999654.ampproject.net
  def.google.com
  d-28678547673442325000.ampproject.net
  i1-j4-20-1-1-13960-2081004232-s.init.cedexis-radar.net
  d-29763453703185417167.ampproject.net
  poi.google.com
  d-3064948553577027059.ampproject.net
  i1-io-0-4-1-20431-1341659986-s.init.cedexis-radar.net
  d-2914631797784843280.ampproject.net
  i1-j1-18-24-1-11326-1053733564-s.init.cedexis-radar.net
  </code></pre>
  
  <p>I want to find the similar common texts and group it. for example, abc.google.com, def.google.com, poi.google.com will point to google.com and etc. </p>
  
  <p>The required output is,</p>
  
  <pre><code>google.com
  ampproject.net
  ampproject.net
  google.com
  ampproject.net
  s.init.cedexis-radar.net
  ampproject.net
  google.com
  ampproject.net
  s.init.cedexis-radar.net
  ampproject.net
  s.init.cedexis-radar.net
  </code></pre>
  
  <p>It's more like a data cleaning exercise where I can clean the unwanted parts. One way is to manually inspect and code for every possible group. But I would be having millions of text. So is there a way / package in python to do this?</p>
  
  <p>Sorry for asking this without trying anything. I've tried to research on this without much success. Not sure how I should start. If anybody can let me know the approach that needs to be taken also, it would be helpful for me.</p>
  
  <p>Thanks</p>