title: Check for each value in column has only one corresponding value in another column pandas
body: <p>I have my data in pandas data frame as follows:</p>
  
  <pre><code>df = pd.DataFrame({'ID': [1234, 1234, 1234, 5678, 5678, 5678, 9999, 9999, 1234, 1234, 1234, 1234],
   'Name': ['AA', 'AA', 'AA', 'BB', 'BB', 'DD', 'EE', 'EE', 'CC', 'CC', 'BB', 'BB'])
  </code></pre>
  
  <pre><code>      ID Name
  0   1234   AA
  1   1234   AA
  2   1234   AA
  3   5678   BB
  4   5678   BB
  5   5678   DD
  6   9999   EE
  7   9999   EE
  8   1234   CC
  9   1234   CC
  10  1234   BB
  11  1234   BB
  </code></pre>
  
  <p>I would like to add another field in this dataframe(with True/False) such that. for each id value, there should be only one corresponding values.</p>
  
  <p>So, my expected output looks like this.. 
  for the id - 1234 there are two corresponding values (AA and BB), the one with lesser count should be flagged.</p>
  
  <pre><code>      ID Name
  5   5678   DD
  8   1234   CC
  9   1234   CC
  10  1234   BB
  11  1234   BB
  </code></pre>