Getting started with R

Data Processing and Visualization in R

Jeff Stevens (he/him)

2025-01-23

What is R?

R is a statistical programming language.

What is R?

R is a statistical programming language.

Source: Allison Horst

What is R?

R is a statistical programming language.

Source: Allison Horst

What is R?

R is a statistical programming language.

Source: Twitter

What is R?

R is a statistical programming language.

It allows you to flexibly

• wrangle data

• visualize data

• analyze data

• create reproducible documents

Conventions

• All code is in monospace font purple text

• R functions end with parentheses: function()

• Directory names end with slash: home/

• Package names are surrounded by curly braces: {tidyverse}

• Keyboard buttons separate keys with a plus: Ctrl+S

• These are parentheses (), brackets [], and braces {}

• Links are in light blue text

Getting started

Installing R

Download at https://r-project.org.

For Windows, also install Rtools

Getting started

Installing RStudio

RStudio is an Integrated Development Environment (IDE). Download from Posit

Getting started

Interacting with R

Using the R console

Packages

Packages are collections of function and data sets

Packages

Base R is a core set of packages for all R installations.

Source: A ModernDive into R and the Tidyverse

Note

User-contributed packages can be found on the Comprehensive R Archive Network or CRAN.

Base R is the core, default software needed to run R maintained by the R Development Team. It includes a few core packages that underly much of R.

But other people can contribute packages, or collections of data and functions.

The official repository for R packages is the Comprehensive R Archive Network or CRAN. There are more than 19,000 packages on CRAN!

Packages can also be stored at other locations such as GitHub especially during development.

Packages

Installing

In the console type

install.packages("<package_name>") where <package_name> is the name of the package.

Packages

Installing

Try installing the {palmerpenguins} package.

install.packages("palmerpenguins")

You can install multiple packages simultaneously by wrapping them with c(). For example,

install.packages(c("remotes", "here"))

Packages

Loading packages

Source: Preceptor’s Primer for Bayesian Data Science

Packages

Loading packages

Load the {here} package:

library("here")

Note

Every time you close your R session, you’ll have to reload the packages you were using.

Installing packages just means that you have copies of them on your computer. You have to load them for R to have access to their functionality. To load packages, use the library() function.

Now, all of the functions in the here package are available for us to use.

Packages

Using

Let’s view the penguins data set from the {palmerpenguins} package.

Try this:

penguins

You should receive Error: object 'penguins' not found. Why did you receive this error?

Once you load a package, you have access to all of its functions for that R session. But if it is not loaded, you won’t have access.

Packages

But you can either load the {palmerpenguins} package, or use this trick to call a specific function from a specific package.

palmerpenguins::penguins

# A tibble: 344 × 8
   species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
   <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
 1 Adelie  Torgersen           39.1          18.7               181        3750
 2 Adelie  Torgersen           39.5          17.4               186        3800
 3 Adelie  Torgersen           40.3          18                 195        3250
 4 Adelie  Torgersen           NA            NA                  NA          NA
 5 Adelie  Torgersen           36.7          19.3               193        3450
 6 Adelie  Torgersen           39.3          20.6               190        3650
 7 Adelie  Torgersen           38.9          17.8               181        3625
 8 Adelie  Torgersen           39.2          19.6               195        4675
 9 Adelie  Torgersen           34.1          18.1               193        3475
10 Adelie  Torgersen           42            20.2               190        4250
# ℹ 334 more rows
# ℹ 2 more variables: sex <fct>, year <int>

tidyverse

Core tidyverse packages

• {ggplot2} for data visualisation

• {dplyr} for data manipulation

• {tidyr} for data tidying

• {readr} for data import

• {tibble} for tibbles, a version of data frames

• {stringr} for strings

• {forcats} for factors

• {lubridate} for dates

• {purrr} for functional programming

Homework

Before the first class period

• Install R from https://r-project.org

• Install RStudio from https://posit.co

• Install {tidyverse} package

• Complete course introduction form

• Read the syllabus

• Read readings in syllabus schedule

Source: Allison Horst