title: Naming returned columns in Pandas aggregate function?
body: <p>I'm having trouble with Pandas' groupby functionality. I've read <a href="http://pandas.pydata.org/pandas-docs/dev/groupby.html" rel="noreferrer">the documentation</a>, but I can't see to figure out how to apply aggregate functions to multiple columns <em>and</em> have custom names for those columns.</p>
  
  <p>This comes very close, but the data structure returned has nested column headings:</p>
  
  <pre><code>data.groupby("Country").agg(
          {"column1": {"foo": sum()}, "column2": {"mean": np.mean, "std": np.std}})
  </code></pre>
  
  <p>(ie. I want to take the mean and std of column2, but return those columns as "mean" and "std")</p>
  
  <p>What am I missing?</p>