title: Use index values to select subset of pandas dataframe
body: <p>With a DataFrame like the following:</p>
  <pre><code>temp = pd.DataFrame({'a':[1,4,7],'b':[2,5,8],'c':[3,6,9]}).T.rename(columns={0:'first_a',1:'first_b',2:'second'})
  
  first_a first_b second
  a   1   4   7
  b   2   5   8
  c   3   6   9
  </code></pre>
  <p>If we want to just subset and use <code>first*</code> columns and filter somehow like the following:</p>
  <pre><code>a = temp.filter(like='first').loc[(temp.filter(like='first') &gt; 4).sum(axis=1) &gt; 0, :]
  
  first_a first_b
  b   2   5
  c   3   6
  </code></pre>
  <p>How can the rest of the information in the original DataFrame be retrieved for the matching samples to return the following:</p>
  <pre><code>first_a first_b second
  b   2   5   8
  c   3   6   9
  </code></pre>
  <p>I tried passing the matching indexes as you would do with a list of column headers but it does not work.</p>