Question

I am attempting to understand why development had shifted from reshape to reshape2 package. They seem to be functionally the same, however, I am unable to upgrade to reshape2 currently due to an older version of R running on the server. I am concerned about the possibility of a major bug that would have shifted development to a whole new package instead of simply continuing development of reshape. Does anyone know if there is a major flaw in the reshape package?

Answer 1

reshape2 let Hadley make a rebooted reshape that was way, way faster, while avoiding busting up people’s dependencies and habits.

https://stat.ethz.ch/pipermail/r-packages/2010/001169.html

Reshape2 is a reboot of the reshape package. It’s been over five years
since the first release of the package, and in that time I’ve learned
a tremendous amount about R programming, and how to work with data in
R. Reshape2 uses that knowledge to make a new package for reshaping
data that is much more focussed and much much faster.

This version improves speed at the cost of functionality, so I have
renamed it to reshape2 to avoid causing problems for existing users.
Based on user feedback I may reintroduce some of these features.

What’s new in reshape2:

• considerably faster and more memory efficient thanks to a much
  better underlying algorithm that uses the power and speed of
  subsetting to the fullest extent, in most cases only making a
  single copy of the data.

• cast is replaced by two functions depending on the output type:
  dcast produces data frames, and acast produces matrices/arrays.

• multidimensional margins are now possible: grand_row and
  grand_col have been dropped: now the name of the margin refers to
  the variable that has its value set to (all).

• some features have been removed such as the | cast operator, and
  the ability to return multiple values from an aggregation function.
  I’m reasonably sure both these operations are better performed by
  plyr.

• a new cast syntax which allows you to reshape based on functions
  of variables (based on the same underlying syntax as plyr):

• better development practices like namespaces and tests.