title: Pandas groupby() not accepting apply() method with options
body: <p>Using the following example:</p>
  
  <pre><code>arrays = [['one','one','one','two','two','two'],[1,2,3,1,2,3]]
  df = pd.DataFrame(np.random.randn(6,2),index=pd.MultiIndex.from_tuples(zip(*arrays)),columns=['A','B'])
  </code></pre>
  
  <p>As expected this apply works over the groupby object:</p>
  
  <pre><code>df.groupby(level=0).apply(lambda x: pd.rolling_mean(x, window=3, center=True))
  </code></pre>
  
  <p>However, when specifying options for apply it throws up an error:</p>
  
  <pre><code>df.groupby(level=0).apply(lambda x: pd.rolling_mean(x, window=3, center=True), raw=True)    
  TypeError: &lt;lambda&gt;() got an unexpected keyword argument 'raw'
  </code></pre>
  
  <p>I can't figure out where I have gone wrong. </p>
  
  <p>Note: It seems to work fine for non MultiIndex objects</p>
  
  <p><a href="https://stackoverflow.com/questions/23100450/pandas-timing-difference-between-function-and-apply-to-series">Pandas: Timing difference between Function and Apply to Series</a></p>