title: Divide certain columns by another column in pandas
body: <p>Was wondering if there is a more efficient way of dividing multiple columns a certain column.  For example say I have:</p>
  
  <pre><code>prev    open    close   volume
  20.77   20.87   19.87   962816
  19.87   19.89   19.56   668076
  19.56   19.96   20.1    578987
  20.1    20.4    20.53   418597
  </code></pre>
  
  <p>And i would like to get:</p>
  
  <pre><code>prev    open    close   volume
  20.77   1.0048  0.9567  962816
  19.87   1.0010  0.9844  668076
  19.56   1.0204  1.0276  578987
  20.1    1.0149  1.0214  418597
  </code></pre>
  
  <p>Basically, columns 'open' and 'close' have been divided by the value from column 'prev.'</p>
  
  <p>I was able to do this by</p>
  
  <pre><code>df['open'] = list(map(lambda x,y: x/y, df['open'],df['prev']))
  df['close'] = list(map(lambda x,y: x/y, df['close'],df['prev']))
  </code></pre>
  
  <p>I was wondering if there is a simpler way?  Especially if there are like 10 columns to be divided by the same value anyways?</p>