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reshape2 is retired: only changes necessary to keep it on CRAN will be made. We recommend using tidyr instead.
Reshape2 is a reboot of the reshape package. It’s been over five years since the first release of reshape, 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 focused 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.
the function melt now names the columns of its
returned data frame Var1, Var2, …,
VarN instead of X1, X2, …,
XN.
the argument variable.name of melt
replaces the old argument variable_name.
Initial benchmarking has shown melt to be up to 10x
faster, pure reshaping cast up to 100x faster, and
aggregating cast() up to 10x faster.
This work has been generously supported by BD (Becton Dickinson).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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