title: pandas - how to merge tables with multiindexes
body: <p>I have two tables that have similar multiindex structure: <code>date</code> and <code>country__name</code>. Indexes are not identical: some of the countries might be missing from one or another table.</p>
  
  <p>The tables have different columns. To illustrate, here they are:</p>
  
  <p><a href="https://i.stack.imgur.com/ESUEC.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/ESUEC.png" alt="One"></a> 
  <a href="https://i.stack.imgur.com/WewBF.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/WewBF.png" alt="two"></a></p>
  
  <p>I want to merge them into one table that keeps the multiindex but has all the columns from both tables. </p>
  
  <p>But when I do</p>
  
  <pre><code>pandas.concat([grouped_channel_df, grouped_tds_df], axis=1)
  </code></pre>
  
  <p>I get a table full of <code>NaN</code>:</p>
  
  <p><a href="https://i.stack.imgur.com/Ze334.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Ze334.png" alt="result"></a></p>
  
  <p>what am I missing?</p>