title: pandas' read_sql with a list of values for WHERE condition
body: <p>Suppose a dataframe <code>scoreDF</code>:</p>
  
  <pre><code>          date       time      score
  sec_code
  1048      2015-02-25 09:21:00     28
  2888      2015-02-25 09:21:00     25
  945       2015-02-25 09:21:00     23
  4         2015-02-25 09:21:00     22
  669       2015-02-25 09:21:00     15
  </code></pre>
  
  <p>I need to make a MySQL query to retrieve all rows matching the values in <code>scoreDF.index</code> i.e. <code>sec_code</code> column.</p>
  
  <p>Normally I'd go for a loop:</p>
  
  <pre><code>    finalResultDF = DataFrame()
  
      queryString = 'SELECT * FROM tableA WHERE sec_code = ' + code
  
      for code in scoreDF.index:
          queryResultDF = sql.read_sql(queryString, con)
          finalResultDF.append(queryResultDF)
  </code></pre>
  
  <p>Would it be possible to do this differently without a loop passing a list of values i.e. <code>scoreDF.index</code> as WHERE condition? I Googled for hours and some mentions 'parameter' to <code>read_sql</code> but I couldn't figure it out.</p>