title: Group by returns empty dataframe and no error
body: <p><strong>I try to <code>groupby</code> and <code>agg</code> but I receive an empty dataframe and no error.</strong></p>
  
  <p>When I do this:</p>
  
  <pre><code>  df_temp = df.groupby('Col1')['InfoType', 'InfoLabel1', 'InfoLabel2'].agg(lambda x: ', '.join(x))
  </code></pre>
  
  <p>then I receive the dataframe aggregated as expected.</p>
  
  <p>When I do this:</p>
  
  <pre><code>  df_temp = df.groupby('Col1', 'Col2')['InfoType', 'InfoLabel1', 'InfoLabel2'].agg(lambda x: ', '.join(x))
  </code></pre>
  
  <p>then I receive the dataframe aggregated as expected.</p>
  
  <p>When I do this:</p>
  
  <pre><code>  df_temp = df.groupby('Col1', 'Col2', 'Col3')['InfoType', 'InfoLabel1', 'InfoLabel2'].agg(lambda x: ', '.join(x))
  </code></pre>
  
  <p>then I receive the dataframe aggregated as expected.</p>
  
  <p>But when I do this:</p>
  
  <pre><code>  df_temp = df.groupby('Col1', 'Col2', 'Col3', 'Col4')['InfoType', 'InfoLabel1', 'InfoLabel2'].agg(lambda x: ', '.join(x))
  </code></pre>
  
  <p>then I receive an empty dataframe and no error.</p>
  
  <p>However, I do not think that the problem is <code>Col4</code> because when I remove <code>Col2</code> and I still keep <code>Col4</code> then I receive the dataframe aggregated as expected.</p>
  
  <p>Why this is happening?</p>
  
  <p>'Col1', 'Col2', 'Col3', 'Col4' are of different types but I do not think that this is the problem because for example also Col1', 'Col2', 'Col3' are of different types but the aggregation works when I group by only on these.</p>
  
  <p>Can it be related to NAs in these columns?</p>
  
  <p>P.S.</p>
  
  <p>I know that it would better to have specific examples of my data but it would be too time-consuming to post them here and also I do not want to expose my data at all.</p>
  
  <p><strong>P.S.2</strong></p>
  
  <p><strong>I did the following. Before the <code>groupby</code>, I filled in the <code>np.nan</code> with values (eg -1 for floats and 'NA' for objects) and the code worked so I was probably right at my initial hypothesis about the NAs. Feel free to share ideas why this is happening.</strong></p>