title: Opposite of dropna() in pandas
body: <p>I have a <code>pandas</code> <code>DataFrame</code> that I want to separate into observations for which there are no missing values and observations with missing values. I can use <code>dropna()</code> to get rows without missing values. Is there any analog to get rows with missing values? </p>
  
  <pre><code>#Example DataFrame
  import pandas as pd
  df = pd.DataFrame({'col1': [1,np.nan,3,4,5],'col2': [6,7,np.nan,9,10],})
  
  #Get observations without missing values
  df.dropna()
  </code></pre>