title: Panda DataFrame.groupby() wierd behaviour with numpy array
body: <p>I have a very big dataframe that I can't put here unlikely for a demonstration but I am wondering if there is an explanation for a problem I have with my code using <code>groupby()</code> method.</p>
  
  <p>So, let <code>df</code> be a numeric <code>pandas.DataFrame</code> with <code>(11815, 409)</code> as shape.</p>
  
  <p>Let <code>arr = df.as_matrix().astype(float)</code>.</p>
  
  <p>Why I have this??</p>
  
  <pre class="lang-py prettyprint-override"><code>print df.groupby(["col1","col2"]).mean().reset_index().shape
  &gt;&gt; (624, 409)
  </code></pre>
  
  <p>While:</p>
  
  <pre class="lang-py prettyprint-override"><code>print pandas.DataFrame(arr).groupby([df["col1"],df["col2"]]).mean().values().shape
  &gt;&gt; (623, 409)
  </code></pre>
  
  <p>Note THAT this problem show up also with <code>["col1","col2","col3"]</code> BUT don't occur with <code>["col2","col3"]</code>,<code>"col1"</code>, <code>"col2"</code> and <code>"col3"</code>.</p>
  
  <p>So, there is a problem with 'col1' but what it can be??</p>
  
  <p>Any explanation please??</p>