title: Convert list of pyodbc.rows to pandas Dataframe takes very long time
body: <p>Is there a faster way to convert pyodbc.rows object to pandas Dataframe? It take about 30-40 minutes to convert a list of 10 million+ pyodbc.rows objects to pandas dataframe. </p>
  
  <pre><code>import pyodbc
  import pandas
  
  server = &lt;server_ip&gt; 
  database = &lt;db_name&gt; 
  username = &lt;db_user&gt; 
  password = &lt;password&gt; 
  port='1443'
  
  conn = pyodbc.connect('DRIVER={SQL Server};SERVER='+server+';PORT='+port+';DATABASE='+database+';UID='+username+';PWD='+ password)
  
  #takes upto 12 minutes
  rows = cursor.execute("select top 10000000 * from [LSLTGT].[MBR_DIM] ").fetchall() 
  
  #Read cursor data into Pandas dataframe.....Takes forever!
  df = pandas.DataFrame([tuple(t) for t in rows]) 
  </code></pre>