title: Using .isin function to produce boolean results of whether a value is listed anywhere in different column
body: <p>Below is a sample dataframe from a much larger set of data. I need to create a new column <code>'Is a Manager?'</code>, that contains boolean results <code>'True'</code> or <code>'False'</code>. The condition; is the <code>'Employee ID'</code> listed anywhere within the <code>'Manager ID'</code> column within the dataset?</p>
  <pre><code>df = pd.DataFrame({'Worker': ['Sam','Tom','Justin','Jake'], 'Employee ID':[12345,12121,67891,99991], 'Manager ID': [97483, 29601,85863, 19739]})
  df
  
      Worker  Employee ID Manager ID
  0   Sam     12345       97483
  1   Tom     12121       29601
  2   Justin  67891       85863
  3   Jake    99991       19739
   and so on....
  </code></pre>
  <p>I have tried to use the <code>.isin</code> function.</p>
  <p>The column was added successfully, but all values state <code>False</code>, when I know some should be <code>True</code>.</p>
  <p>For example, Sam's Employee ID <code>12345</code> is listed on line 245 as person X's manager <code>'Manager ID' = 12345</code></p>
  <p>Any idea where i've gone wrong? My code is:</p>
  <pre><code>df3 = df.loc[:, ['Worker', 'Employee ID', 'Manager ID']]
  df3.insert(1, 'Is a Manager?', df3['Employee ID'].isin(['Manager ID']))
  df3
  
  Worker  Is a Manager?   Employee ID Manager ID
  0   A      False       221113      1210236
  1   B      False       221359      86082653
  2   C      False       295142      1718020
  3   D      False       775199      1910236
  </code></pre>