- install.packages(pkgs, lib, repos, method, destdir, dependencies, ...)
|pkgs||character vector of the names of packages. If |
|lib||character vector giving the library directories where to install the packages.|
|repos||character vector, the base URL(s) of the repositories to use, can be |
|destdir||directory where downloaded packages are stored|
|dependencies||logical indicating whether to also install uninstalled packages which these packages depend on/link to/import/suggest (and so on recursively). Not used if |
|...||Arguments to be passed to ‘download.file’ or to the functions for binary installs on OS X and Windows.|
Download and install packages from repositories
Packages are collections of R functions, data, and compiled code in a well-defined format. Public (and private) repositories are used to host collections of R packages. The largest collection of R packages is available from CRAN.
A package can be installed from CRAN using following code:
"dplyr" is referred to as a character vector.
More than one packages can be installed in one go by using the combine function
c() and passing a series of character vector of package names:
install.packages(c("dplyr", "tidyr", "ggplot2"))
In some cases,
install.packages may prompt for a CRAN mirror or fail, depending on the value of
getOption("repos"). To prevent this, specify a CRAN mirror as
install.packages("dplyr", repos = "https://cloud.r-project.org/")
repos argument it is also possible to install from other repositories.
For complete information about all the available options, run
Most packages require functions, which were implemented in other packages (e.g. the package
data.table). In order to install a package (or multiple packages) with all the packages, which are used by this given package, the argument
dependencies should be set to
install.packages("data.table", dependencies = TRUE)
Bioconductor hosts a substantial collection of packages related to Bioinformatics. They provide their own package management centred around the
## Try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite()
By default this installs a subset of packages that provide the most commonly used functionality. Specific packages can be installed by passing a vector of package names. For example, to install
RImmPort from Bioconductor:
Install local development version of a package
While working on the development of an R package it is often necessary to install the latest version of the package. This can be achieved by first building a source distribution of the package (on the command line)
R CMD build my_package
and then installing it in R. Any running R sessions with previous version of the package loaded will need to reload it.
A more convenient approach uses the
devtools package to simplify the process. In an R session with the working directory set to the package directory
will build, install and reload the package.
Install package from local source
To install package from local source file:
install.packages(path_to_source, repos = NULL, type="source") install.packages("~/Downloads/dplyr-master.zip", repos=NULL, type="source")
path_to_source is absolute path of local source file.
Another command that opens a window to choose downloaded zip or tar.gz source files is:
Another possible way is using the GUI based RStudio:
Step 1: Go to Tools.
Step 2: Go to Install Packages.
Step 3: In the Install From set it as Package Archive File (.zip; .tar.gz)
Step 4: Then Browse find your package file (say crayon_1.3.1.zip) and after some time (after it shows the Package path and file name in the Package Archive tab)
Another way to install R package from local source is using
install_local() function from devtools package.
Install packages from GitHub
To install packages directly from GitHub use the
ggplot2 from github:
The above command will install the version of
ggplot2 that corresponds to the master branch. To install from a different branch of a repository use the
ref argument to provide the name of the branch. For example, the following command will install the
dev_general branch of the
devtools::install_github("SymbolixAU/googleway", ref = "dev_general")
Another option is to use the
ghit package. It provides a lightweight alternative for installing packages from github:
To install a package that is in a private repository on Github, generate a personal access token at http://www.github.com/settings/tokens/ (See ?install_github for documentation on the same). Follow these steps:
config = httr::config(ssl_verifypeer = FALSE)
install.packages("RCurl") options(RCurlOptions = c(getOption("RCurlOptions"),ssl.verifypeer = FALSE, ssl.verifyhost = FALSE ) )
You should see the following:
ssl.verifypeer ssl.verifyhost FALSE FALSE
library(httr) set_config(config(ssl_verifypeer = 0L))
This prevents the common error: "Peer certificate cannot be authenticated with given CA certificates"
Finally, use the following command to install your package seamlessly
Alternatively, set an environment variable
Sys.setenv(GITHUB_PAT = "access_token") devtools::install_github("organisation/package_name")
The PAT generated in Github is only visible once, i.e., when created initially, so its prudent to save that token in
.Rprofile. This is also helpful if the organisation has many private repositories.
Using a CLI package manager -- basic pacman usage
pacman is a simple package manager for R.
pacman allows a user to compactly load all desired packages, installing any which are missing (and their dependencies), with a single command,
pacman does not require the user to type quotation marks around a package name. Basic usage is as follows:
p_load(data.table, dplyr, ggplot2)
The only package requiring a
install.packages statement with this approach is
library(pacman) p_load(data.table, dplyr, ggplot2)
or, equally valid:
pacman::p_load(data.table, dplyr, ggplot2)
In addition to saving time by requiring less code to manage packages,
pacman also facilitates the construction of reproducible code by installing any needed packages if and only if they are not already installed.
Since you may not be sure if
pacman is installed in the library of a user who will use your code (or by yourself in future uses of your own code) a best practice is to include a conditional statement to install
pacman if it is not already loaded:
if(!(require(pacman)) install.packages("pacman") pacman::p_load(data.table, dplyr, ggplot2)