How to use the command R (with examples)

How to use the command R (with examples)

R is a programming language and software environment for statistical computing and graphics. It provides a wide variety of statistical and graphical techniques and is highly extensible. This article will illustrate several use cases of the R command.

Use case 1: Start a REPL (interactive shell)

Code:

R

Motivation: Starting an R REPL allows users to interact with the R language in real-time. It is useful for exploring data, testing code snippets, and executing R commands on the fly.

Explanation: Simply typing R in the command line will start the R interpreter in an interactive shell mode.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things"
...
Type 'q()' to quit R.
> 

Use case 2: Check R version

Code:

R --version

Motivation: Knowing the version of R installed on your system is important for compatibility and troubleshooting purposes. This use case allows you to quickly check the installed R version.

Explanation: Running R --version will display the version information of the R interpreter installed on your system.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things" 
...

Use case 3: Start R in vanilla mode

Code:

R --vanilla

Motivation: Sometimes you may want to start a clean and fresh R session without any saved workspace from previous sessions. The vanilla mode ensures that no saved objects or settings interfere with your current session.

Explanation: With the --vanilla option, running R will start a blank R session that doesn’t save the workspace at the end.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things" 
...
Type 'q()' to quit R.
> 

Use case 4: Execute a file

Code:

R -f path/to/file.R

Motivation: Executing an R script file is helpful when you have a pre-written R code that you want to run without manually typing each command in the terminal.

Explanation: By using the -f option followed by the path to an R script file, you can execute the contents of the file using the R interpreter.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things" 
...
[1] "Hello, World!"

Use case 5: Execute an R expression and then exit

Code:

R -e expr

Motivation: Running a single R expression from the command line can be useful for quick calculations or evaluations without the need to open the full R interpreter.

Explanation: With the -e option followed by an R expression, you can execute the specified expression and then exit the R interpreter.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things" 
...
[1] 14.3

Use case 6: Run R with a debugger

Code:

R -d debugger

Motivation: Running R with a debugger can help identify and debug issues in your R code. It allows you to step through the execution of your script, set breakpoints, and inspect variables.

Explanation: Using the -d option followed by a specified debugger, you can run R code with debugging functionality enabled.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things" 
...
Debugging session initiated at ...
Browse[2]> 

Use case 7: Check R packages from package sources

Code:

R CMD check path/to/package_source

Motivation: Verifying the integrity and correctness of an R package from its source files is important before sharing or publishing the package. The R CMD check command helps to ensure that the package meets the required standards.

Explanation: Running R CMD check followed by the path to the package source files allows you to perform checks on the package and report any issues or errors.

Example output:

R version 4.1.1 (2021-08-10) -- "Kick Things" 
...
* checking DESCRIPTION meta-information ... OK
* checking for LF line-endings in source and make files
* checking for empty or unneeded directories

Conclusion:

This article covered various use cases of the R command, demonstrating how to start a REPL, check the R version, start R in vanilla mode, execute files and expressions, run R with a debugger, and check R packages from package sources. By understanding and utilizing these use cases, you can efficiently work with the R programming language and its environment.

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