R on RStudio

Introduction to R and RStudio

R is a powerful programming language and software environment specifically designed for statistical computing and data analysis. It provides a platform for data manipulation, calculation, statistical analysis and data visualisation.

RStudio is an integrated development environment (IDE) for R, providing a user-friendly interface that enhances the R programming experience

Installation Guide

  1. Download and install R from https://cran.rstudio.com/
  2. Download and install RStudio from https://posit.co/download/rstudio-desktop/
    • If you have already installed R and RStudio for some time, you might want to update them.
      • Update RStudio: Locate Help tab in RStudio and click Check for Updates. If it’s not the latest version, download and install RStudio again using the link above.
      • Update R: Run the following commands on RGui:
install.packages("installr")
library(installr)
updateR()

If prompted to choose CRAN mirrors, just select any of the Australian for the fastest installation.

  1. Install recommended packages by running the installation.packages() command on the RStudio Console or locating Tools tab and then Install Packages.
Package Description
swirl Free R interactive lessons right in the Rconsole
tidyverse Collection of packages designed for data science
rmarkdown Creating dynamic documents in R. Combine text, code, and output in a single document.
knitr, markdown, tinytex Enhance R Markdown experience (knitr: report generating engine, markdown: HTML conversion package,tinytex: LaTeX distribution (optional)

To collectively install every recommended packages at once:

install.packages(c("swirl", "tidyverse", "rmarkdown", "knitr", "markdown", "tinytex"))

Installation of Rtools is optional.

  1. Setting up a working environment

    • Create a new project under your directory: File β†’ New Project. The Output pane (bottom right panel) will now switch to Files tab, showing your current directory.
    • Create a new R Notebook or download lab sheet ws01-r.Rmd from BB and save it.
    • (Optional setup) In the top-left of the notebook interface, tick Preview on Save box.
    • (Optional setup) In the top-left of the notebook interface, click on the setting/gear icon β†’ Preview in Viewer Pane

  2. To convert an R Notebook (an .Rmd file) to an HTML file, you can use the β€œKnit” button in RStudio or the rmarkdown::render() function in the R console.

    • Also, ensure that your document has the correct YAML header. For an HTML output, the YAML metadata at the top of your file should look something like this:
---
title: "My Notebook"
output: html_notebook
---

User Interface

References

R R Core Team. (2024). R: A language and environment for statistical computing. https://www.r-project.org/

RStudio Posit Software, PBC. (2024). RStudio: Integrated development environment for R. https://posit.co/products/open-source/rstudio/

R Markdown Allaire, J. J., Xie, Y., McPherson, J., et al. (2024). R Markdown: Dynamic documents for R. https://rmarkdown.rstudio.com/

knitr Xie, Y. (2024). knitr: A general-purpose package for dynamic report generation in R. https://yihui.org/knitr/

Markdown Gruber, J. (2024). Markdown. https://daringfireball.net/projects/markdown/

tinytex Xie, Y. (2024). tinytex: A lightweight, cross-platform, and portable LaTeX distribution. https://yihui.org/tinytex/

tidyverse Wickham, H., Averick, M., Bryan, J., et al. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686

swirl Kross, S., & Carchedi, D. (2024). swirl: Learn R, in R. https://swirlstats.com/