title: Simple way to remove special characters and alpha numerical from dataframe
body: <p>I have a large dataset with some x rows and y number of columns. one of the columns as words and some unwanted data. That unwanted data is has no specific pattern hence I am finding it difficult to remove that from the dataframe. </p>
  
  <pre><code>nonhashtag
  ['want', 'better', 'than', 'Dhabi,', 'United', 'Arab', 'Emirates']
  ['Just', 'posted', 'photo', 'Rasim', 'Villa']
  ['Dhabi', 'International', 'Airport', '(AUH)', '\xd9\x85\xd8\xb7\xd8\xa7\xd8\xb1', '\xd8\xa3\xd8\xa8\xd9\x88', '\xd8\xb8\xd8\xa8\xd9\x8a', '\xd8\xa7\xd9\x84\xd8\xaf\xd9\x88\xd9\x84\xd9\x8a', 'Dhabi']
  ['just', 'shrug', 'off!', 'Dubai', 'Mall', 'Burj', 'Khalifa']
  ['out!', 'Cowboy', 'steppin', 'Notorious', 'going', 'sleep!', 'Make', 'happen']
  ['Buona', 'notte', '\xd1\x81\xd0\xbf\xd0\xbe\xd0\xba\xd0\xbe\xd0\xb9\xd0\xbd\xd0\xbe\xd0\xb9', '\xd0\xbd\xd0\xbe\xd1\x87\xd0\xb8', '\xd9\x84\xd9\x8a\xd9\x84\xd8\xa9', '\xd8\xb3\xd8\xb9\xd9\x8a\xd8\xaf\xd8\xa9!', '\xd8\xa3\xd8\xa8\xd9\x88', '\xd8\xb8\xd8\xa8\xd9\x8a', 'Viceroy', 'Hotel,', 'Yas\xe2\x80\xa6']
  </code></pre>
  
  <p>Every character which is not a word is to be removed this is only one column in the large dataset. Column name is <code>nonhashtag</code></p>
  
  <p>What is the simple way to clean the column. straight away remove them or replace with <code>NAN</code></p>
  
  <p>Expected output </p>
  
  <pre><code>nonhashtag
      ['want', 'better', 'than', 'Dhabi,', 'United', 'Arab', 'Emirates']
      ['Just', 'posted', 'photo', 'Rasim', 'Villa']
      ['Dhabi', 'International', 'Airport', '(AUH)', 'Dhabi']
      ['just', 'shrug', 'off!', 'Dubai', 'Mall', 'Burj', 'Khalifa']
      ['out!', 'Cowboy', 'steppin', 'Notorious', 'going', 'sleep!', 'Make', 'happen']
      ['Buona', 'notte', 'Viceroy', 'Hotel,']
  </code></pre>
  
  <p>Every <code>[]</code> is one row in that particular column so removing of only the <code>\x and remaining characters</code> is needed the empty <code>[]</code> should be left in the row. Keeping the row is important as other column's that row is filled with needed information. </p>
  
  <p>To write a proper code I couldn't get pass through the input read as I am not able to find a pattern in the dataset to write a regex. </p>
  
  <p>Thanks in advance for the help </p>