title: Pandas aggregation ignoring NaN's
body: <p>I aggregate my Pandas dataframe: <code>data</code>. Specifically, I want to get the average and sum <code>amount</code>s by tuples of [<code>origin</code> and <code>type</code>]. For averaging and summing I tried the numpy functions below:</p>
  
  <pre><code>import numpy as np
  import pandas as pd
  result = data.groupby(groupbyvars).agg({'amount': [ pd.Series.sum, pd.Series.mean]}).reset_index() 
  </code></pre>
  
  <p>My issue is that the <code>amount</code> column includes <code>NaN</code>s, which causes the <code>result</code> of the above code to have a lot of <code>NaN</code> average and sums. </p>
  
  <p>I know both <code>pd.Series.sum</code> and <code>pd.Series.mean</code> have <code>skipna=True</code> by default, so why am I still getting <code>NaN</code>s here?</p>
  
  <p>I also tried this, which obviously did not work:</p>
  
  <pre><code>data.groupby(groupbyvars).agg({'amount': [ pd.Series.sum(skipna=True), pd.Series.mean(skipna=True)]}).reset_index() 
  </code></pre>
  
  <p><strong>EDIT:</strong> 
  Upon @Korem's suggestion, I also tried to use a <code>partial</code> as below:</p>
  
  <pre><code>s_na_mean = partial(pd.Series.mean, skipna = True)    
  data.groupby(groupbyvars).agg({'amount': [ np.nansum, s_na_mean ]}).reset_index() 
  </code></pre>
  
  <p>but get this error:</p>
  
  <pre><code>error: 'functools.partial' object has no attribute '__name__'
  </code></pre>