These packages provide a comprehensive foundation for creating and using models of all types. Tidymodels packages, which largely replace the If you’d like to learn how to use the tidyverse effectively, the best place to start is R for data. The tidyverse package is designed to make it easy to install and load core packages from the tidyverse in a single command. Modeling with the tidyverse uses the collection of The tidyverse is a set of packages that work in harmony because they share common data representations and API design. Paste() that makes it easier to combine data and strings. Piping operators (like %$% and %%) that can be useful in other places.
It also provide a number of more specialised Purrr, which provides very consistent and natural methods for iterating on R objects, there are two additional tidyverse packages that help with general programming challenges: dbplyr allows you to use remote database tables by converting dplyr code into SQL.ĭata.table backend by automatically translating to the equivalent, but usually much faster, data.table code.There are also two packages that allow you to interface with different backends using the same dplyr syntax: You’ll need to pair DBI with a database specific backends likeĭplyr, there are five packages (includingįorcats) which are designed to work with specific types of data: Readr, for reading flat files, the tidyverse package installs a number of other packages for reading data: They are not loaded automatically with library(tidyverse), so you’ll need to load each one with its own call to library(). The tidyverse also includes many other packages with more specialised usage. R uses factors to handle categorical variables, variables that have a fixed and known set of possible values. Orphaned Packages with no active maintainer, see the corresponding README.Forcats provides a suite of useful tools that solve common problems with factors. Related Directories Archive Previous versions of the packages listed above, and other packages formerly available. New packages and how to contribute them to CRAN.ĭescribes the policies in place for the CRAN package repository. (also contained in the R base sources) explains how to write In R for information on how to install packages from thisĪll packages are tested regularly on machines running They provide tools to automatically install all packages from each view. Table of available packages, sorted by nameĬRAN Task Views aim to provide some guidance which packages on CRAN are relevant for tasks related to a certain topic. Table of available packages, sorted by date of publication Currently, the CRAN package repository features 19400 available packages.
0 kommentar(er)
