R — Get Started

Install R

First, install the R language itself:

1. Go to cran.r-project.org
2. Download the installer for your operating system
3. Run it and accept the defaults

On Mac, you may also need to install XQuartz for some packages. On Linux, use your package manager.

Verify the installation

Open a terminal and type:

R --version

You should see the version number. The latest stable version is recommended.

Install RStudio

RStudio is the standard IDE for R development:

1. Go to posit.co/download/rstudio-desktop
2. Download the free version
3. Install and launch

RStudio gives you a console, editor, file browser, plotting pane, variable viewer, and package manager — everything in one window.

The R console

When you open RStudio, you see the console. Type commands directly:

> 2 + 2
[1] 4

> "Hello, world!"
[1] "Hello, world!"

> seq(1, 5)
[1] 1 2 3 4 5

The > is the prompt. [1] indicates the first element of the output. R always shows element indices when printing vectors.

R scripts

Real work happens in scripts — saveable files with .R extension:

1. In RStudio, click File → New File → R Script
2. Type your code
3. Press Ctrl+Enter (or Cmd+Enter on Mac) to run the current line
4. Save with Ctrl+S

# my_first_script.R

# Assign values
name <- "Ada"
age <- 36

# Print
cat("Hello,", name, "! You are", age, "years old.\n")

Assignment

R uses <- for assignment (not =, though = also works):

x <- 5        # preferred style
y = 10        # also works, but not R convention

x <- 10       # reassign — x is now 10

The <- operator reads as "gets" — x gets the value 5. This is R's community convention. Some style guides allow = but <- is the standard.

Installing packages

R's power comes from packages. Install them from CRAN:

# Install a package (one-time)
install.packages("ggplot2")

# Load it for use
library(ggplot2)

• install.packages() downloads and installs from CRAN
• library() loads the package into your current session
• You only install once; you load every session

Essential packages

# Data manipulation
install.packages(c("dplyr", "tidyr", "readr"))

# Visualization
install.packages(c("ggplot2", "scales"))

# Data import
install.packages(c("readxl", "jsonlite"))

# Development
install.packages(c("devtools", "roxygen2"))

Getting help

# Search help
?mean              # opens help page for mean
??linear regression  # searches for "linear regression"

# Examples
example(plot)       # runs the examples from the plot help page

# Arguments of a function
args(mean)

R's help system is comprehensive. Every function has a help page with description, usage, arguments, and examples.

Working directory

R runs commands relative to a working directory:

# Check current directory
getwd()

# Set a new directory
setwd("/path/to/project")

# List files
list.files()

In RStudio, set the working directory via Session → Set Working Directory.

Reading data

# CSV file
data <- read.csv("data.csv")

# Excel file (requires readxl)
library(readxl)
data <- read_excel("data.xlsx")

# Built-in datasets
data(mtcars)
head(mtcars)

R has built-in datasets for learning: mtcars, iris, airquality, faithful, and more.

Basic exploration

# Load a built-in dataset
data(iris)

# Structure
str(iris)

# Summary statistics
summary(iris)

# Dimensions
dim(iris)    # 150 rows, 5 columns

# First few rows
head(iris)

# Column names
names(iris)

# Class
class(iris)  # "data.frame"

RStudio shortcuts

Shortcut	Action
Ctrl+Enter	Run current line
Ctrl+Shift+Enter	Run entire script
Ctrl+Enter	In console: run and advance
Ctrl+L	Clear console
Ctrl+Shift+C	Toggle comment
Tab	Autocomplete
F1	Help for selected function

Mini Practice

1. Install R and RStudio, verify both are working
2. In the console, calculate 100 * 365 and sqrt(144)
3. Create a new R script and assign your name and age to variables
4. Install the ggplot2 package and load it
5. Load the built-in mtcars dataset and run summary(mtcars)

Next: R syntax rules →