title: Selecting all columns with at least one value above threshold
body: <p>I want to select <em>columns</em> which have <em>at least</em> one value above the threshold. 
  For example, </p>
  
  <pre><code>df = pd.DataFrame({'A': [randint(1, 9) for x in xrange(10)],
                     'B': [randint(1, 9)*10 for x in xrange(10)],
                     'C': [randint(1, 9)*100 for x in xrange(10)]})
  df
     A   B    C
  0  9  40  300
  1  9  70  700
  2  5  70  900
  3  8  80  900
  4  7  50  200
  5  9  30  900
  6  2  80  700
  7  2  80  400
  8  5  80  300
  9  7  70  800
  </code></pre>
  
  <p>Lets say I want to select columns which contain at least one value >70.
  In this case I'd expect to see as an output the following dataframe</p>
  
  <pre><code>   df
         B    C
      0  40  300
      1  70  700
      2  70  900
      3  80  900
      4  50  200
      5  30  900
      6  80  700
      7  80  400
      8  80  300
      9  70  800
  </code></pre>
  
  <hr>
  
  <p>The only solution I can come up with is to loop through every column, see if there are any values above a threshold(for example, using <code>.any()</code>) and then pass an array of columns to <code>.filter()</code>... but that feels like a very awkward solution. Is there a better way? </p>