title: Large, persistent DataFrame in pandas
body: <p>I am exploring switching to python and pandas as a long-time SAS user.  </p>
  
  <p>However, when running some tests today, I was surprised that python ran out of memory when trying to <code>pandas.read_csv()</code> a 128mb csv file.  It had about 200,000 rows and 200 columns of mostly numeric data.</p>
  
  <p>With SAS, I can import a csv file into a SAS dataset and it can be as large as my hard drive. </p>
  
  <p>Is there something analogous in <code>pandas</code>? </p>
  
  <p>I regularly work with large files and do not have access to a distributed computing network.</p>