title: how to remove rows that contain NaN in both 1st and 3rd columns?
body: <p>When dataframe is like this,</p>
  <pre><code>      a    b     c     d
  0   1.0  NaN   3.0   NaN
  1   NaN  6.0   NaN   8.0
  2   9.0  NaN   NaN   NaN
  3  13.0  NaN  15.0  16.0
  </code></pre>
  <p>I want to remove rows that contain NaN in <strong>both</strong> b and d columns. So I want the result to be like this.</p>
  <pre><code>      a    b     c     d
  1   NaN  6.0   NaN   8.0
  3  13.0  NaN  15.0  16.0
  </code></pre>
  <p>In this situation I can't use <code>df.dropna(thresh=2)</code> because I don't want to erase row 1, <br/>
  and if I use <code>df.dropna(subset=['b', 'd'])</code> then row 3 will be removed too.<br/>
  What should I do now?</p>