plyr is a set of tools that solves a common set of problems: you need
to break a big problem down into manageable pieces, operate on each
pieces and then put all the pieces back together. It's already
possible to do this with split and the apply functions, but plyr just
makes it all a bit easier with:
* 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
* the choice of passing chunks as rows or as variables
plyr functions are named according to the type of object they input
(first letter) and output (second letter):
* llply = from a list to a list
* alply = from an array (or vector, or matrix) to a list
* ldply = from a list to a data.frame
* d_ply = from a data.frame, ignore output
* and so on for llply, laply, ldply, l_ply, alply, aaply, adply,
a_ply, dlply, daply, dply, d_ply
plyr also provides:
* m*ply which works in a similar way to mapply
* r*ply which works in a similar way to replicate
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.
Regards,
Hadley
--
http://had.co.nz/
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