Meet the toolkit: R and RStudio



Data visualization and transformation

Data Science with R

Learning goals

By the end of the course, you will be able to…

  • gain insights from data

  • gain insights from data, using modern programming tools and techniques

  • gain insights from data, using modern programming tools and techniques, reproducibly with literate programming

  • gain insights from data, using modern programming tools and techniques, reproducibly with literate programming and version control

By the end of the course, you will be able to…

  • gain insights from data

  • gain insights from data, using modern programming tools and techniques

  • gain insights from data, using modern programming tools and techniques, reproducibly with literate programming

  • gain insights from data, using modern programming tools and techniques, reproducibly with literate programming and version control

R and RStudio

  • Open-source statistical programming language
  • Also an environment for statistical computing and graphics

  • Convenient interface for R called an IDE (integrated development environment), e.g. “I write R code in the RStudio IDE”
  • Not a requirement for programming with R, but it’s very commonly used by R programmers and data scientists

R vs. RStudio

“engine”

“dashboard”

R packages

  • Packages are the fundamental units of reproducible R code – they include reusable R functions, documentation of these functions, and sample data

  • Packages are how the community extends R

  • As of April 2024, there are over 20,000 R packages available on CRAN (the Comprehensive R Archive Network)

  • We’re going to work with a small (but important) subset of these!

Let’s take a tour of

    and    

Tour recap: R and RStudio


A short list (for now) of R essentials

  • Functions are (most often) verbs, followed by what they will be applied to in parentheses:
do_this(to_this)
do_that(to_this, to_that, with_those)
  • Packages are installed with the install.packages() function and loaded with the library function, once per session:
install.packages("package_name")
library(package_name)

R essentials (continued)

  • Columns (variables) in data frames are accessed with $:
dataframe$var_name
  • Object documentation can be accessed with ? 
?mean

tidyverse

tidyverse.org

  • The tidyverse is an opinionated collection of R packages designed for data science

  • All packages share an underlying philosophy and a common grammar

Acknowledgements