In this module, we will learn about R packages. There are ~12000 packages available on CRAN or the Comprehensive R Archive Network. Packages are available for different topics and you should always look for a package before writing code from scratch. In case you have written your own codes for a new analysis or topic, do share it with the R community by converting the R scripts into a package. You can learn more about building R packages from R Packages, a book written by Hadley Wickham.
In this post, we will learn to:
Packages from CRAN can be installed using
install.packages(). The name of the package must be enclosed in single or double quotes.
Some R packages are made available on GitHub before releasing them on CRAN. Such packages can be installed using
install_github() from devtools or remotes package. You need to specify the name of the repository and the package. For example, to download ggplot2 or dplyr, below is the code:
Bitbucket is similar to GitHub. You can install packages from Bitbucket using
install_bitbucket() from devtools or remotes pacakge.
Bioconductor provides tools for analysis and comprehension of high throughput genomic data. Packages hosted on Bioconductor can be installed in multiple ways:
install_bioc() from devtools.
Many R packages are hosted at R-Forge, a platform for development of R packages.
install.packages('quantstrat', repos = 'https://r-forge.r-project.org/')
Now that we have learnt how to install packages, let us look at installing different versions of the same package.
remotes::install_version('dplyr', version = 0.5.0)
If you want to install the latest release from GitHub, append
@*release to the repository name. For example, to install the latest release of dplyr:
||View currently installed packages.|
||Load package into the current R session.|
||List of packages available for installation.|
||List of packages which have new versions available.|
||List of packages already not installed.|
||Update packages which have new versions available.|
||Remove installed packages.|
Library is a directory that contains all installed packages. Usually there will be more than one R library in your systme. You can find the location of the libraries using
##  "C:/Users/HP/Documents/R/win-library" ##  "C:/Program Files/R/R-3.5.0/library"
You can use
lib.loc when you want to install, load, update and remove packages from a particular library.
To use the functionalities offered by a package, we must load it into the current R session. Use
library() to load a R package and specify the location of the package using the
library(lubridate, lib.loc = "C:/Program Files/R/R-3.4.1/library")