Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>),
  Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>),
  RStudio [cph, fnd]

Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou,
 Nathan Russell, Douglas Bates and John Chambers

The 'Rcpp' package provides R functions as well as C++ classes which
 offer a seamless integration of R and C++. Many R data types and objects can be
 mapped back and forth to C++ equivalents which facilitates both writing of new
 code as well as easier integration of third-party libraries. Documentation
 about 'Rcpp' is provided by several vignettes included in this package, via the
 'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and
 Francois (2011, <doi:10.18637/jss.v040.i08>), the book by Eddelbuettel (2013,
 <doi:10.1007/978-1-4614-6868-4>) and the paper by Eddelbuettel and Balamuta (2018,
 <doi:10.1080/00031305.2017.1375990>); see 'citation("Rcpp")' for details.

RUnit, inline, rbenchmark, knitr, rmarkdown, pinp, pkgKitten
(>= 0.1.2)

Please send questions and comments regarding Rcpp to
rcpp-devel@lists.r-forge.r-project.org

c(
    person("Kirill", "Müller", , "krlmlr+r@mailbox.org", role = c("aut", "cre")),
    person("Hadley", "Wickham", role = "aut"),
    person("RStudio", role = "cph")
  )

Provides 'pillar' and 'colonnade' generics designed for formatting columns
   of data using the full range of colours provided by modern terminals.

'capital.R' 'compat-lifecycle.R' 'compat-purrr.R' 'dim.R'
'empty-data.R' 'extent.R' 'lengths.R' 'multi.R' 'ornament.R'
'pillar-package.R' 'pillar.R' 'rowid-capital.R' 'rowid-data.R'
'rowid-title.R' 'rowid-type.R' 'scientific.R' 'shaft.R'
'shaft-simple.R' 'sigfig.R' 'spark-bar.R' 'spark-line.R'
'strrep.R' 'styles.R' 'testthat.R' 'tick.R' 'title.R'
'type-sum.R' 'type.R' 'utils.R' 'vctrs.R' 'width.R' 'zzz.R'

Kirill Müller [aut, cre],
  Hadley Wickham [aut],
  RStudio [cph]

Tools for Splitting, Applying and Combining Data

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'.