title: Pandas to_sql replace duplicates
body: <p>I am making request to API every second with parameter since(to return changes since last request) I convert it to dataframe and would like quickly insert it into MySQL with replacement of duplicate rows something like this:</p>
  
  <pre><code>REPLACE INTO table (column1,column2...) VALUES (val1,val2...) 
  </code></pre>
  
  <p>I really like function <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_sql.html" rel="nofollow">DataFrame.to_sql</a> but the problem is that it does not have replace duplicate rows option. The way I can see with DataFrame.to_sql is to drop table each time and recreate it with option if_exists: replace, but I think it will influence performance significantly. Can you advise what is the better way to insert data from dataframe with replacement of duplicate values?</p>