title: Keeping "None Dataframes" when using DataFrame's Groupby
body: <p>I have a list of dataframes, and some are None (they don't have any value).
  But when I DO: </p>
  
  <pre><code>dict_of_dfs = dict(enumerate([LIST OF DATAFRAMES]))
  dframes = pd.concat(dict_of_dfs)
  </code></pre>
  
  <p>However, when I perform (this is to get normalised tables):</p>
  
  <pre><code>test = dframes.groupby(level=1).pipe(lambda g: dframes.sub(g.mean(), level=1).div(g.std(), level=1))
  </code></pre>
  
  <p>It looks like it's getting rid of these None dataframes.</p>
  
  <p>Because I then use:</p>
  
  <pre><code>tmpList=[]
  for date, new_df in test.groupby(level=0):
      tmpList.append(new_df)
  </code></pre>
  
  <p>This final "tmpList" will be a shorter list than my first one.</p>
  
  <p>How can I do?
  I basically want to transform a list of dataframes (which includes None dataframe) into a same list of dataframes (which are all normalised now).</p>