title: Pandas groupby(df.index) with indexes of varying size
body: <p>I have an array of dataframes <code>dfs = [df0, df1, ...]</code>. Each one of them have a <code>date</code> column of varying size (some <code>date</code>s might be in one dataframe but not the other).</p>
  
  <p>What I'm trying to do is this:</p>
  
  <pre><code>pd.concat(dfs).groupby("date", as_index=False).sum()
  </code></pre>
  
  <p>But with date no longer being a column but an index (<code>dfs = [df.set_index("date") for df in dfs]</code>).</p>
  
  <p>I've seen you can pass <code>df.index</code> to <code>groupby</code> (<code>.groupby(df.index)</code>) but <code>df.index</code> might not include all the dates.</p>
  
  <p>How can I do this?</p>
  
  <p>The goal here is to call <code>.sum()</code> on the <code>groupby</code>, so I'm not tied to using <code>groupby</code> nor <code>concat</code> is there's any alternative method to do so.</p>