title: Pandas: selecting multiple groups for inset plot
body: <p>I have a group data frame (<code>grouped_df</code>) used for plotting in the following way:</p>
  
  <pre><code>grouped_df[['col1','col2','col3']].sum().plot(kind='bar')
  </code></pre>
  
  <p>resulting in the expected plot, which contains a group-wise sum for all three columns. However, for some of the groups these sums are very small compared to the rest and hence not easy to display in the same bar plot (see image below). </p>
  
  <p>I want to have an inset plot for these groups. Trying,</p>
  
  <pre><code>grouped_df[['col1','col2','col3']].sum() &lt; "cut-off"
  </code></pre>
  
  <p>returns a boolean "list" of these groups but I cannot use any further for slicing/selection the a subset of groups of the data frame.</p>
  
  <p>Of course, I could generate two lists of groups and then loop through the <code>grouped_df</code> but I do not think this is really a bright solution to the problem.</p>
  
  <p><a href="https://i.stack.imgur.com/ccuqt.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/ccuqt.png" alt="Example"></a></p>
  
  <p>For clarity and consistence I provide a sample data frame which would be grouped by <code>grpcol</code>:</p>
  
  <pre><code>grpcol    col1     col2     col3     comment          
  A         0.0505   0.0134   0.0534   foo
  B         0.0505   0.0134   0.2034   bar
  A         0.0505   0.0134   0.0134   bar
  C         0.0505   0.0134   0.0331   None
  D         0.0505   0.0134   0.0342   foo
  E         0.0505   0.0134   0.2134   baz
  F         0.0505   0.0134   0.0302   baz
  D         0.0302   0.0134   0.2134   foo
  D         0.0204   0.0134   0.0400   foo
  G         0.0505   0.0134   0.2200   foo
  H         0.0505   0.0134   0.1734   None
  H         0.0505   0.0134   0.0073   None
  </code></pre>