title: Is there a more efficient way to load 10,000 excel rows into python?
body: <p>I am loading data from excel to populate objects ie teacher(lastName, firstName, user_ID). These teacher objects are then put into a list, where further manipulation and analysis is done (ie looking for matches and other patterns). My approach to do this was use the xlrd module to load the data from excel. </p>
  
  <pre><code>for row in range(11) :
      lastName = sheet1.cell_value(row,3)
      firstName = sheet1.cell_value(row,1)
      userID = sheet1.cell_value(row,0)
      profList.append(tempProf)
  </code></pre>
  
  <p>So this method takes my computer like 20 seconds to do for just 12 rows and I need to do this for 10,000. My question- is there another way to load in data like this in a more efficient manner? I am open to out scoping, so if this question sounds stupid, I would love to hear alternatives, thanks  </p>