Suggests: abind, testthat, tcltk, foreach, doMC, itertools, iterators

Title: Tools for Splitting, Applying and Combining Data
Description: 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
piece and then put all the pieces back together.  For example, you might
want to fit a model to each spatial location or time point in your study,
summarise data by panels or collapse high-dimensional arrays to simpler
summary statistics. The development of 'plyr' has been generously supported
Suggests: abind, testthat, tcltk, foreach, doParallel, itertools,

Description: 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 piece and then put all the pieces back together.  For
example, you might want to fit a model to each spatial location or
time point in your study, summarise data by panels or collapse
high-dimensional arrays to simpler summary statistics. The development
of 'plyr' has been generously supported by 'Becton Dickinson'.
Suggests: abind, covr, doParallel, foreach, iterators, itertools,

Description: 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
piece and then put all the pieces back together.  For example, you
might want to fit a model to each spatial location or time point in
your study, summarise data by panels or collapse high-dimensional
arrays to simpler summary statistics. The development of 'plyr' has
been generously supported by 'Becton Dickinson'.
Packaged: 2022-03-24 19:18:45 UTC; hadleywickham

Packaged: 2022-11-11 16:45:00 UTC; hadleywickham

Suggests: abind, testthat (>= 0.2), tcltk, foreach, doMC, itertools,
Collate: 'dimensions.r' 'id.r' 'indexed-array.r' 'indexed-data-frame.r'
'indexed.r' 'join.r' 'loop-apply.r' 'progress.r' 'quote.r'
'data.r' 'plyr.r' 'parallel.r' 'progress-time.r' 'a_ply.r'
'aaply.r' 'adply.r' 'alply.r' 'd_ply.r' 'daply.r' 'ddply.r'
'dlply.r' 'l_ply.r' 'laply.r' 'llply.r' 'm_ply.r' 'maply.r'
'mdply.r' 'mlply.r' 'r_ply.r' 'raply.r' 'rdply.r' 'rlply.r'
'liply.r' 'ldply.r' 'arrange.r' 'colwise.r' 'count.r'
'data-frame.r' 'defaults.r' 'each.r' 'here.r' 'match-df.r'
'mutate.r' 'name-rows.r' 'quickdf.r' 'rename.r' 'revalue.r'
'round-any.r' 'splat.r' 'strip-splits.r' 'summarise.r' 'take.r'