title: How to load only specific columns from csv file into a DataFrame
body: <p>Suppose I have a csv file with 400 columns.  I cannot load the entire file into a DataFrame (won't fit in memory).  However, I only really want 50 columns, and this will fit in memory.  I don't see any built in Pandas way to do this.  What do you suggest?  I'm open to using the <code>PyTables</code> interface, or <code>pandas.io.sql</code>.  </p>
  
  <p>The best-case scenario would be a function like:  <code>pandas.read_csv(...., columns=['name', 'age',...,'income'])</code>.  I.e. we pass a list of column names (or numbers) that will be loaded.</p>