title: Change Pandas index datatype on MultiIndex
body: <p>I have a Pandas dataframe with two indexes</p>
  
  <pre><code>                              Column1
  indexA   indexB                        
  1001     aaa                        1
           bbb                        1
           ccc                        1
           ddd                        1
  </code></pre>
  
  <p>created by</p>
  
  <pre><code>pd.read_sql(sql=sql, index_col=['indexA', 'indexB'])
  </code></pre>
  
  <p>MySQL is reading in <code>indexB</code> as unicode and I would like to convert it to a string. My goal is to pivot the table and have the entries in <code>indexB</code> be the column names. When I do this with the unicode values I get the following column names:</p>
  
  <pre><code>�  �  �  �  �  �  �  �  �
  </code></pre>
  
  <p>when running</p>
  
  <pre><code>pd.read_sql(sql=sql, index_col=['indexA', 'indexB']).unstack().fillna(0)
  </code></pre>
  
  <p><strong>EDIT:</strong> A comment suggested the following:</p>
  
  <pre><code>df = pd.read_sql(sql)
  df['indexB'] = df['indexB'].astype(str)
  df = df.set_index(('indexA', 'indexB'), drop=True)
  </code></pre>
  
  <p>which is a nice work around to my problem (thank you). Would still be nice to know if this can be done during initialization. </p>