title: Generate a new pandas Dataframe composed of the Unique userIDs and the mode in the other columns
body: <p>So my dataframe looks like this.</p>
  
  <pre><code>userID.   A.   B.   C
    1.      X.   O.   1   
    2.      X.   N.   2
    1.      X.   O.   3
    1.      Y.   O.   4
  </code></pre>
  
  <p>Each unique User ID's could occur any number of times. What I'm trying to do is to generate a new Pandas Dataframe where each row contains a unique ID for userID, and the values for columns A,B,C are the mode for each of those unique users. If mode is tied for any column, any of those tied values is fine. For example below is what I'm looking for.</p>
  
  <pre><code>userID.   A.   B.   C
    1.      X.   O.   1
    2.      X.   N.   2
  </code></pre>
  
  <p>I saw a similar post here (<a href="https://stackoverflow.com/questions/55409848/find-the-mode-of-multiple-columns-for-each-unique-value">Find the mode of multiple columns for each unique value</a>)  But this isn't exactly what I'm looking for.</p>
  
  <p>More complex Example</p>
  
  <pre><code>UserID.       A.   B.   C
        1.      Y.   O.   1   
        2.      X.   N.   2
        1.      X.   O.   3
        1.      Y.   O.   4
        1.      X.   O.   1   
        2.      X.   N.   2
        1.      X.   O.   3
        1.      Y.   O.   4
        1.      X.   O.   1   
        2.      X.   N.   2
        1.      X.   O.   3
        1.      Y.   O.   4
  </code></pre>
  
  <p>Will give the same result:</p>
  
  <pre><code>userID.   A.   B.   C
    1.      X.   O.   1
    2.      X.   N.   2
  </code></pre>
  
  <p>EDIT: Note that I used X,0, 1 for values. In reality the values could be str, float, ints.</p>