title: Pandas Merge: The column label is not unique
body: <p>Considering two tables: one which contains all the indices, and another which contains data for some indices. The purpose is to have an entry for all index, regardless of it having data, and if it does, then add it. Similar to a <code>LEFT OUTER JOIN</code> in SQL.
  The indices table, named <code>dates</code>, could be something like:</p>
  
  <pre><code>     name week
  0  name_0    0
  1  name_0    1
  2  name_0    2
  3  name_0    3
  4  name_0    4
  5  name_0    5
  6  name_1    0
  7  name_1    1
  8  name_1    2
  </code></pre>
  
  <p>so the table would contain 6 weeks for <code>name_0</code>, and 3 weeks for <code>name_1</code>.
  Whereas the data table, named <code>data_holes</code>, could be:</p>
  
  <pre><code>     name week otherdata
  0  name_0    1         2
  1  name_0    2         5
  2  name_0    5        20
  3  name_1    1         5
  </code></pre>
  
  <p>The desired merge result would be:</p>
  
  <pre><code>name week other_data
  0  name_0    0     N/A
  1  name_0    1      2
  2  name_0    2      5
  3  name_0    3     N/A    
  4  name_0    4     N/A
  5  name_0    5      20
  6  name_1    0     N/A
  7  name_1    1     N/A
  8  name_1    2      5
  </code></pre>
  
  <p>However, when using <code>dates.merge(data_holes, how='left', on=['name','week'])</code> I am faced with an error:</p>
  
  <blockquote>
    <p>ValueError: The column label 'week' is not unique.</p>
  </blockquote>