title: pandas group by ALL functionality?
body: <p>I'm using the <code>pandas groupby+agg</code> functionality to generate nice reports</p>
  
  <pre><code>aggs_dict = {'a':['mean', 'std'], 'b': 'size'}
  df.groupby('year').agg(aggs_dict)
  </code></pre>
  
  <p>I would like to use the same <code>aggs_dict</code> on the entire dataframe as a single group, with no division to years, something like:</p>
  
  <pre><code>df.groupall().agg(aggs_dict)
  </code></pre>
  
  <p>or:</p>
  
  <pre><code>df.agg(aggs_dict)
  </code></pre>
  
  <p>But couldn't find any elegant way to do it.. Note that in my real code <code>aggs_dict</code> is quite complex so it's rather cumbersome to do:</p>
  
  <pre><code>df.a.mean()
  df.a.std()
  df.b.size()
  ....
  </code></pre>
  
  <p>am I missing something simple and nice?</p>