title: How to select rows with one or more nulls from a pandas DataFrame without listing columns explicitly?
body: <p>I have a dataframe with ~300K rows and ~40 columns.
  I want to find out if any rows contain null values - and put these 'null'-rows into a separate dataframe so that I could explore them easily.</p>
  
  <p>I can create a mask explicitly:</p>
  
  <pre><code>mask = False
  for col in df.columns: 
      mask = mask | df[col].isnull()
  dfnulls = df[mask]
  </code></pre>
  
  <p>Or I can do something like:</p>
  
  <pre><code>df.ix[df.index[(df.T == np.nan).sum() &gt; 1]]
  </code></pre>
  
  <p>Is there a more elegant way of doing it (locating rows with nulls in them)?</p>