Chapter 1 Download RStudio & Basics of R

1.1 Setting up RStudio

Why use R for data visualization?

• R is free.
• Often, less codes are needed in R to plot an elegant graph.
• for/while loops (basic concepts in programming) are not necessary in R to make a production-quality graph.
• R is the best software for statistical analysis.

Other available resources for R

• Stack Overflow: https://www.stackoverflow.com
• R for Data Science (a bible for learning R): https://r4ds.had.co.nz/
• R documentation: https://www.rdocumentation.org
• Learn Statistics with R: https://learningstatisticswithr.com/
• ggplot2 (a reference for plotting data in R): https://ggplot2-book.org/

Download requirements for RStudio

• Download R: http://cran.r-project.org/
• For Mac users: Mac: XQuartz https://www.xquartz.org/
• RStudio: http://www.rstudio.org/

Open RStudio

Figure 1.1: Rstudio layout, image from http://www.sthda.com/english/wiki/running-rstudio-and-setting-up-your-working-directory-easy-r-programming

• Rstudio is where people do R programming.
• You can type codes (commands) into the console (bottom-left panel).
  • > means that the console is ready to receive more code.
  • + means your code is not complete.
• You can also write (longer) codes in the script within the code editor (top-left panel).
  • The code editor will run the script into the console.
  • A new script can be opened by clicking: File -> New -> R Script.
• You can run a script by clicking ’Run” with the green arrow or by typing ctrl + enter. It is labeled with the red circle.
  • Or you can just type your codes directly into the console.

Let’s make a folder and set it as working directory

Figure 1.2: Setting your working directory, image from https://www.ucl.ac.uk/~uctqiax/PUBLG100/2015/faq/setwd.html

• Create a folder named LearnR in Desktop.
• Set the folder as your working directory by clicking: Session -> Set Working Directory -> Choose Directory. Then find your LearnR folder.
• More information about setting up a directory is here: http://www.sthda.com/english/wiki/running-rstudio-and-setting-up-your-working-directory-easy-r-programming
• You will need set the directory every time you start RStudio.

1.1.1 How to run your code

• You can run code in 2 ways.

• First, you can type it in the script and run it after highlighting the codes you would like to run.

Figure 1.3: How to run your code - script

• Second, you can type your code directly in the console.

Figure 1.4: How to run your code - console

1.2 Basics of R

Let’s type some codes

• Capitalization, punctuations and brackets are all important.
• ' ' and " " mean the same.
• However, ' " are not paired. So they will not work.
• = and <- mean equivalent.
  • I often use <-.
• Type ? when you are not sure about the code (ex. ?t.test)
• A code becomes comment when it is preceded by #.
  • Try typing # g = 3 and see if the number gets stored in g by typing g in the console.

x = 3 # x equals to 3
a <- 4 # a equals to 4 
d <- 'Group' # gr is equal to a character 'Group', which is not a number.
e <- "Group"
d == e # 'Group' and "Group" are equal

## [1] TRUE

# g = 3 # its a comment

• Notice that I used == to test if d and e are equal. Therefore, == and = mean different. == tests if two things are equal. = sets two things to be equal.
  • d == e returns TRUE because they are both 'Group'. TRUE is equivalent to 1 numerically.
• Now let’s check if x and a are equal.

x == a

## [1] FALSE

• It returns FALSE because x and a are not equal. This is correct because 3 and 4 are not equal. FALSE equals to 0 numerically.

• Below are more examples showing that TRUE = 1 and FALSE = 0.

TRUE + FALSE # 1 + 0

## [1] 1

TRUE + TRUE # 1 + 1

## [1] 2

FALSE + FALSE # 0 + 0

## [1] 0

TRUE*2 # 1 * 2

## [1] 2

TRUE*FALSE # 1 * 0

## [1] 0

How can I learn most effectively with the notes?

• Don’t just read it.
• Don’t just copy and paste the codes and run them in RStudio (ctrl + c & ctrl + p). Make sure you type each code.
• You can also change your code and see if it still works.
• If you are not sure of your code, you can type ? before the function.
• If you are still not sure after reading the notes, check out Chapter 3 of R for Data Science: https://r4ds.had.co.nz/

More installation

• R is an old programming language.
• So, people, such as statisticians and programmers, have created more functions in R in the form of the package to update the language. They are free but they have to be downloaded separately.
  • A package can contain several functions.
  • In this tutorial, you will mainly be using ggplot2 package, which is elegant and flexible for visualizing data.
  • Also, you will be using smplot package. It improves ggplot2 graphs visually.
• So, you will need to install some packages, such as ggplot2 and smplot. Please type the codes below.

install.packages('devtools')
devtools::install_github('smin95/smplot', force = TRUE) # requires VPN if you are in China

• You only need to install them once, but you will need to reload them whenever you start a new session in RStudio using the function library().

install.packages('tidyverse') # only need to install once
install.packages('cowplot')

# packages must be loaded every time by using library() when you run your script

library(tidyverse) # it has ggplot2 package
library(cowplot) # it allows you to save figures in .png file
library(smplot)

• Now let’s make some graphs in the subsequent chapters.