title: Must produce aggregated value. I swear that I am
body: <p>consider the <code>pd.Series</code> <code>s</code></p>
  
  <pre><code>a = np.arange(4)
  mux = pd.MultiIndex.from_product([list('ab'), list('xy')])
  s = pd.Series([a] * 4, mux)
  print(s)
  
  a  x    [0, 1, 2, 3]
     y    [0, 1, 2, 3]
  b  x    [0, 1, 2, 3]
     y    [0, 1, 2, 3]
  dtype: object
  </code></pre>
  
  <hr>
  
  <p><strong><em>problem</em></strong><br>
  each element of <code>s</code> is a <code>numpy.array</code>.  when I try to sum within groups, I get an error because the groupby function expects the result to be scalar... (I'm guessing)</p>
  
  <pre><code>s.groupby(level=0).sum()
  </code></pre>
  
  <blockquote>
  <pre><code>Exception                                 Traceback (most recent call last)
  &lt;ipython-input-627-c5b3bf6890ea&gt; in &lt;module&gt;()
  ----&gt; 1 s.groupby(level=0).sum()
  
  C:\Anaconda2\lib\site-packages\pandas\core\groupby.pyc in f(self)
      101             raise SpecificationError(str(e))
      102         except Exception:
  --&gt; 103             result = self.aggregate(lambda x: npfunc(x, axis=self.axis))
      104             if _convert:
      105                 result = result._convert(datetime=True)
  
  C:\Anaconda2\lib\site-packages\pandas\core\groupby.pyc in aggregate(self, func_or_funcs, *args, **kwargs)
     2584                 return self._python_agg_general(func_or_funcs, *args, **kwargs)
     2585             except Exception:
  -&gt; 2586                 result = self._aggregate_named(func_or_funcs, *args, **kwargs)
     2587 
     2588             index = Index(sorted(result), name=self.grouper.names[0])
  
  C:\Anaconda2\lib\site-packages\pandas\core\groupby.pyc in _aggregate_named(self, func, *args, **kwargs)
     2704             output = func(group, *args, **kwargs)
     2705             if isinstance(output, (Series, Index, np.ndarray)):
  -&gt; 2706                 raise Exception('Must produce aggregated value')
     2707             result[name] = self._try_cast(output, group)
     2708 
  
  Exception: Must produce aggregated value
  </code></pre>
  </blockquote>
  
  <hr>
  
  <p><strong><em>work around</em></strong><br>
  when I use <code>apply</code> with <code>np.sum</code>, it works fine.</p>
  
  <pre><code>s.groupby(level=0).apply(np.sum)
  
  a    [0, 2, 4, 6]
  b    [0, 2, 4, 6]
  dtype: object
  </code></pre>
  
  <hr>
  
  <p><strong><em>question</em></strong><br>
  is there an elegant way to handle this?</p>
  
  <hr>
  
  <p><strong><em>real problem</em></strong><br>
  I actually want to use <code>agg</code> in this way</p>
  
  <pre><code>s.groupby(level=0).agg(['sum', 'prod'])
  </code></pre>
  
  <p>but it fails in the same way.<br>
  the only way to get this is to</p>
  
  <pre><code>pd.concat([g.apply(np.sum), g.apply(np.prod)],
            axis=1, keys=['sum', 'prod'])
  </code></pre>
  
  <p><a href="https://i.stack.imgur.com/1108f.png" rel="noreferrer"><img src="https://i.stack.imgur.com/1108f.png" alt="enter image description here"></a></p>
  
  <p>but this doesn't generalize well to longer lists of transforms.</p>