title: Selecting a subset using dropna() to select multiple columns
body: <p>I have the following DataFrame:</p>
  
  <pre><code>df = pd.DataFrame([[1,2,3,3],[10,20,2,],[10,2,5,],[1,3],[2]],columns = ['a','b','c','d'])
  </code></pre>
  
  <p>From this DataFrame, I want to drop the rows where all values in the subset ['b', 'c', 'd'] are NA, which means the last row should be dropped.</p>
  
  <p>The following code works:</p>
  
  <pre><code>df.dropna(subset=['b', 'c', 'd'], how = 'all')
  </code></pre>
  
  <p>However, considering that I will be working with larger data frames, I would like to select the same subset using the range  ['b':'d']. How do I select this subset?</p>