title: How to calculate aggregated summary statistics in Pandas dataframe
body: <p>I have a Pandas dataframe similar to this: </p>
  
  <pre><code>&gt;&gt;&gt; df = pd.DataFrame(data=np.array([['red', 'cup', 1.50], ['blue', 'jug', 2.40], ['red', 'cup', 1.75], ['blue', 'cup', 2.30]]),
  ...                   columns=['colour', 'item', 'price'])
  &gt;&gt;&gt; df
    colour item price
  0    red  cup   1.5
  1   blue  jug   2.4
  2    red  cup  1.75
  3   blue  cup   2.3
  </code></pre>
  
  <p>What is the most concise way to calculate the summary statistics of the price for each of the possible combinations of colour and item?</p>
  
  <p>Expected output e.g.:</p>
  
  <pre><code>colour     item      mean     stdev
  red        cup       1.625    0.176
  blue       jug       2.4      NA
  blue       cup       2.3      NA
  </code></pre>