title: Error in read.csv with colClasses: scan() expected 'a real' got 'NULL'
body: <p>I am reading in large csv file using <code>read.csv</code>. Several websites suggest using colClasses to define the classes for each column to make the import process faster.</p>
  
  <pre><code>t = read.csv("pca.csv",header=TRUE,colClasses = classes)
  Error in scan(file, what, nmax, sep, dec, quote, skip, nlines, na.strings,  : 
  scan() expected 'a real', got 'NULL'
  
  classes = c("numeric","integer")
  </code></pre>
  
  <p>I obviously have nulls in some of my data.  Is there a way to use colClasses where "numeric" or "integer" include nulls? Also, any other tips on importing large datasets faster into R would be very helpful.  I have all the data in a SQL database and I've tried using RODBC which is surprisingly slower than read.csv().</p>