plyr is a set of tools for a common set of problems: you need to break down a big data structure into manageable pieces, operate on each piece and then put all the pieces back together.  For example, you might want to:
 
  * fit the same model to subsets of a data frame
  * quickly calculate summary statistics for each group
  * perform group-wise transformations like scaling or standardising
  * eliminate for-loops in your code
 
It's already possible to do this with built-in functions (like split and the apply functions), but plyr just makes it all a bit easier with:
 
  * absolutely consistent names, arguments and outputs
  * input from and output to data.frames, matrices and lists
  * progress bars to keep track of long running operations
  * built-in error recovery, and informative error messages
 
Some considerable effort has been put into making plyr fast and memory efficient, and in most cases it is faster than the built-in functions.
 
You can find out more at http://had.co.nz/plyr/, including a 20 page introductory guide, http://had.co.nz/plyr/plyr-intro.pdf.  You can ask questions about plyr (and data-manipulation in general) on the plyr mailing list.  Sign up at http://groups.google.com/group/manipulatr