Installing R on Debian
A Debian 9 system with at least 1G of RAM and sudo privileges is all that is needed to get started on installing R. R is an open-source programming language designed for statistical computing and graphical representation, managed by the R Foundation for Statistical Computing.
R is a popular language among statisticians and data miners due to its wide range of functionalities. To install R on Debian, the first step is to add the CRAN repository to the list of apt sources by running the following command:
$ sudo echo “deb https://cloud.r-project.org/bin/linux/debian stretch-cran35/” >> /etc/apt/sources.list
The next step is to update the apt sources list and install R:
$ sudo apt-get update
$ sudo apt-get install r-base
Once the installation of R is complete, R packages can now be installed from CRAN.
Installing R Packages from CRAN
The Comprehensive R Archive Network (CRAN) provides a vast library of R packages to users. Installing R packages can be done via the R console or through the system terminal.
To install R packages from the R console, open R by typing:
$ sudo -i R
To install the build-essential package, run:
> install.packages(“build-essential”)
To install the stringr package globally, run:
> install.packages(“stringr”)
Alternatively, R packages can be installed through the system terminal using the following command:
$ sudo apt-get install r-cran-stringr
It is recommended to install R packages globally using the system terminal. However, if the package is for personal use only, it is possible to install the R package in a personal library by running:
> .libPaths(“~/R-packages”)
> install.packages(“stringr”, lib = “~/R-packages”)
R Programming
Starting R Console
To start the R console, open the terminal and type:
$ sudo -i R
This opens up the R console with access to R functions and packages. Users can create variables to store data and perform operations on data using R functions.
Running Functions
One of the primary features of R programming is its vast collection of functions designed to process and analyze data. Functions in R are used to perform specific tasks or operations on data, similar to functions in other programming languages.
To get started with R functions, users can create a character vector and use the str_length() function to determine the length of each string in the vector. > x <- c("apple", "banana", "cherry", "date")
> str_length(x)
The output of this function would be:
[1] 5 6 6 4
This shows the length of each string in the character vector.
Available R Packages
R has a vast collection of packages available through the CRAN repository. These packages can be easily installed and loaded into the R environment, providing access to a wide range of functionality and capabilities.
To install an R package, users can use the install.packages() function and specify the package name. > install.packages(“ggplot2”)
This command installs the ggplot2 package and makes it available for use within the R environment.
Conclusion
R is a powerful programming language designed for statistical computing and graphical representation. Installing R on a Debian 9 system is a straightforward process that involves adding the CRAN repository to the apt sources list and installing R through the system terminal.
R packages can also be installed from CRAN, providing access to a vast collection of additional functionality and capabilities. Users can get started with R programming by simply opening the R console and running R functions or installing and loading R packages.
In summary, this article provides an informative guide on how to install R on Debian 9 and get started with R programming. The steps to install R on Debian involve adding the CRAN repository and installing R, while installing R packages from CRAN can be done via the R console or system terminal.
R programming involves starting the R console, running R functions, and accessing a vast collection of R packages. R is a powerful programming language that statisticians and data miners use for statistical computing and graphical representation.
The article emphasizes the importance of R programming in data science and encourages readers to explore the possibilities of R in their work or projects.