title: How to use nunique value counts of a single column after groupby to apply some condition?
body: <p>I want to save the ids into a list which have nunique() value counts greater than some threshold. </p>
  
  <p><code>temp=df.groupby('id')['random_column'].nunique().sort_values(ascending=False)</code></p>
  
  <p>The above command gives all ids with their unique count values but the <em>count_values</em> do not have any column_name due to which when I try to put some condition for eg. <code>temp[temp.random_column&gt;1]</code>,</p>
  
  <p>I get </p>
  
  <p><code>AttributeError: 'Series' object has no attribute 'random_column'</code>.</p>
  
  <p>But, when I add another column in the entire command, I don't get above error:
  <code>temp=df.groupby('id')['random_column', 'one_more_column'].nunique()</code></p>
  
  <p><code>temp[temp.random_column&gt;1]</code> works fine.</p>
  
  <p>Why can't I use a single column to do the same?</p>