title: pandas dataframe column name: remove special character
body: <p>Some joker made a Lotus database/applet thingy for tracking engineering issues in our company.  The joke is that the key piece of information was named with a special character... a number sign (hash tag, pound sign, \u0023).</p>
  
  <p>abbreviated sample:</p>
  
  <pre><code>KA#         Issue Date      Current Position
  27144       1/9/2014        Accounting
  27194       12/20/2012      Engineering
  32474       4/21/2008       Engineering
  32623-HOLD  4/25/2016       Engineering
  32745       11/13/2012      SEPE
  32812       10/30/2013      Engineering
  32817       12/7/2012       Purchasing
  32839       1/8/2013        SEPE
  </code></pre>
  
  <p>I output this table (4K rows, 15 columns) to a csv file and process in python3 as a pandas dataframe.</p>
  
  <p>I generate various outputs.  If I use something like:</p>
  
  <pre><code>df.iloc[:,[0,3,1,8,9,10]]
  </code></pre>
  
  <p>I get appropriate output and the key column shows up as <code>"KA#"</code>. (When I say "key column", I mean "most important"... NOT "index".  I keep a serial index)</p>
  
  <p>Unfortunately, people sometimes mess with the column order in Lotus between my exports to csv so I can not guarantee that <code>"KA#"</code> will be any particular column number.  I would like to use column names:</p>
  
  <pre><code>df.loc[:,["KA#","Issue Date","Current Position"]]
  </code></pre>
  
  <p>But the <code>"KA#"</code> column is filled with NaN's.</p>
  
  <p>Thanks for any help you can offer.</p>
  
  <p>Finally, if I try to rename <code>"KA#"</code> to simply <code>"KA"</code>:</p>
  
  <pre><code>df['KA#'].name = 'KA'
  </code></pre>
  
  <p>throws a KeyError and</p>
  
  <pre><code>df = df.rename(columns={"KA#": "ka"})
  </code></pre>
  
  <p>is completely ignored.  The column shows up as <code>"KA#"</code>.</p>
  
  <p>Can anyone think of a way to get rid of or handle that symbol?  I'd even settle for a regex at this point.</p>