title: Transforming dataframe string categories to numbers
body: <p>I have some columns in my dataframe that look like:</p>
  
  <pre><code> total
    NaN
  26-27
  52-53
  88-89
    165
    280
    399
    611
    962
   1407
   1937
  </code></pre>
  
  <p>I would like to transform them into numerical values using a round-up:</p>
  
  <pre><code> total
    NaN
     27
     53
     89
    165
    280
    399
    611
    962
   1407
   1937
  </code></pre>
  
  <p>clearly, pd.to_numeric() does not work as 26-27 is an object. I can do it one by one, but is there an elegant and fast way to do the transformation?</p>