reshape

An R package to flexible rearrange, reshape and aggregate data

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R

reshape2

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Status

Lifecycle: superseded

reshape2 is superseded: only changes necessary to keep it on CRAN will be made. We recommend using tidyr instead.

Introduction

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).