title: Python Pandas calculating log returns between rows
body: <p>I have a dataframe containing prices indexed by date.  Is there a way to calculate the log return from one day to the next?</p>
  <p>So if my original dataframe looks like this:</p>
  <pre><code>            BBG.XSTO.FABG.S BBG.XETR.BIO3.S BBG.XPAR.BOL.S  BBG.XMCE.AIR.S  
  date                
  03/02/2014  8.785104        81.151          3.938           51.4627
  04/02/2014  8.805004        81.151          4.142           51.4627
  05/02/2014  8.866988        82.007          4.197           50.5261
  06/02/2014  9.038363        82.135          4.162           51.4134
  07/02/2014  8.978838        83.512          4.126           51.7585
  </code></pre>
  <p>How can I apply the formula:</p>
  <pre><code>log(today_price / yesterday_price)
  </code></pre>
  <p>so I get something that looks like:</p>
  <pre><code>            BBG.XSTO.FABG.S BBG.XETR.BIO3.S BBG.XPAR.BOL.S  BBG.XMCE.AIR.S  
  date                
  03/02/2014  na               na             na              na
  04/02/2014  0.002262636      0              0.050505783     0
  05/02/2014  0.007014971      0.010492993    0.013191221    -0.018367239
  06/02/2014  0.019142907      0.001559626    -0.008374256    0.017408804
  07/02/2014  -0.006607599     0.016626099    -0.008687313    0.006689831
  </code></pre>