Los 10 principales competidores de r-pkgs.org

cran.r-project.org

Provides tools for working with multiple related tables, stored as data frames or in a relational database. Multiple tables (data and metadata) are stored in a compound object, which can then be manipulated with a pipe-friendly syntax.

devtools.r-lib.org

Collection of package development tools.

pkgdown.r-lib.org

Designed to be run as part of automated workflows for deploying to GitHub pages. It cleans out the old site, builds the site into dest_dir adds a .nojekyll file to suppress rendering by Jekyll, and adds a CNAME file if needed. It is designed to be run in CI, so by default it: Cleans out the old site. Does not install the package. Runs build_site() in process.

roxygen2.r-lib.org

Learn the full details in vignette('rd-other'). Key tags: @field ${1:name} ${2:description}: Describe a R6 or refClass field. @format ${1:description}: Describe the type/shape of a dataset. If the dataset is a data frame, include a description of each column. If not supplied, will be automatically generated by object_format(). @method ${1:generic} ${2:class}: Force a function to be recognised as an S3 method. This affects the default usage and the NAMESPACE directive produced by @export. Only needed if automatic detection fails. @slot ${1:name} ${2:description}: Describe the slot of an S4 class. @source ${1:description}: Describe where the dataset came from. Provide a link to the original source (if possible) and briefly describe any manipulation that you performed when importing the data.

usethis.r-lib.org

use_tidy_labels() has been replaced by use_tidy_github_labels(). use_tidy_ci() has been replaced by use_tidy_github_actions(). use_tidy_eval() is defunct because there's no longer a need to systematically import and re-export a large number of functions in order to use tidy evaluation. Instead, use use_import_from() to tactically import functions as you need them.

pak.r-lib.org

Please take a look at this list before asking questions.

testthat.r-lib.org

See https://adv-r.hadley.nz/oo.html for an overview of R's OO systems, and the vocabulary used here. expect_type(x, type) checks that typeof(x) is type. expect_s3_class(x, class) checks that x is an S3 object that inherits() from class expect_s3_class(x, NA) checks that x isn't an S3 object. expect_s4_class(x, class) checks that x is an S4 object that is() class. expect_s4_class(x, NA) checks that x isn't an S4 object. expect_r6_class(x, class) checks that x an R6 object that inherits from class. expect_s7_class(x, Class) checks that x is an S7 object that S7::S7_inherits() from Class See expect_vector() for testing properties of objects created by vctrs.

contributions.bioconductor.org

Most packages contributed by users are software packages. However, there are instances where other package types are submitted. The following sections will go into specifics we look for in each of...

kbroman.org

Materials for spring, 2018, seminar course in Plant Breeding at UW-Madison

varianceexplained.org

I recently came across this question on Cross Validated, and I thought it offered a great opportunity to use R and ggplot2 to explore, in depth, the assumptions underlying the k-means algorithm. The question, and my response, follow.