Large, persistent DataFrame in pandas
You can use Pytable rather than pandas df.
It is designed for large data sets and the file format is in hdf5.
So the processing time is relatively fast.
I am exploring switching to python and pandas as a long-time SAS user.  
However, when running some tests today, I was surprised that python ran out of memory when trying to pandas.read_csv() a 128mb csv file.  It had about 200,000 rows and 200 columns of mostly numeric data.
With SAS, I can import a csv file into a SAS dataset and it can be as large as my hard drive. 
Is there something analogous in pandas? 
I regularly work with large files and do not have access to a distributed computing network.