Hands On Exercise 2

Beyond ggplot2 Fundamentals

Published

April 22, 2025

Modified

May 1, 2025

There are several ggplot2 extensions for creating more elegant and effective statistical graphics. Let’s explore these features!

Getting Started

Besides tidyverse, four R packages will be used.

  • ggrepel: to provide geoms for ggplot2 to repel overlapping text labels

  • ggthemes: to provide extra themes, geoms, and scales for ‘ggplot2’

  • hrbrthemes: for typography-centric themes and theme components for ggplot2

  • patchwork: for preparing composite figure created using ggplot2

To check if these packages have been installed and to load them into your working R environment, run the code below.

Code 
pacman::p_load(ggrepel, patchwork, ggthemes, hrbrthemes, tidyverse)

Importing Data

The code chunk below imports exam_data.csv into R environment by using read_csv() function of readr package. 

Code 
exam_data <- read_csv("Exam_data.csv")
show_col_types = FALSE
knitr::kable(head(exam_data))
ID CLASS GENDER RACE ENGLISH MATHS SCIENCE
Student321 3I Male Malay 21 9 15
Student305 3I Female Malay 24 22 16
Student289 3H Male Chinese 26 16 16
Student227 3F Male Chinese 27 77 31
Student318 3I Male Malay 27 11 25
Student306 3I Female Malay 31 16 16

What is ggrepel?

One of the challenge in plotting statistical graph is annotation, especially with large number of data points. Take a look below and see it for yourself.

Code 
ggplot(data=exam_data, 
       aes(x= MATHS, 
           y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, 
              size=0.5) +  
  geom_label(aes(label = ID), 
             hjust = .5, 
             vjust = -.5) +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100)) +
  ggtitle("English scores versus Maths scores for Primary 3")

Code 
knitr::opts_chunk$set(warning = FALSE)

ggrepel is an extension of ggplot2 package which provides geoms for ggplot2 to repel overlapping text.

Code 
ggplot(data=exam_data, 
       aes(x= MATHS, 
           y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, 
              size=0.5) +  
  geom_label_repel(aes(label = ID), 
                   fontface = "bold") +
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100)) +
  ggtitle("English scores versus Maths scores for Primary 3")

Code 
knitr::opts_chunk$set(warning = FALSE)

Themes

ggplot2 comes with eight built-in themes, they are: theme_gray(), theme_bw(), theme_classic(), theme_dark(), theme_light(), theme_linedraw(), theme_minimal(), and theme_void().

Code 
ggplot(data=exam_data, 
             aes(x = MATHS)) +
  geom_histogram(bins=20, 
                 boundary = 100,
                 color="grey25", 
                 fill="#630e27") +
  theme_dark() +
  ggtitle("Distribution of Maths Scores")

Code 
knitr::opts_chunk$set(warning = FALSE)
Code 
ggplot(data=exam_data, 
             aes(x = MATHS)) +
  geom_histogram(bins=20, 
                 boundary = 100,
                 color="grey25", 
                 fill="#630e27") +
  ggtitle("Distribution of Maths scores") +
  theme_ipsum()

Code 
knitr::opts_chunk$set(warning = FALSE)

Combining Graphs

Let’s create three graphs named p1, p2 and p3.

Code 
p1 <- ggplot(data=exam_data, 
             aes(x = MATHS)) +
  geom_histogram(bins=20, 
                 boundary = 100,
                 color="grey25", 
                 fill="#630e27") + 
  coord_cartesian(xlim=c(0,100)) +
  ggtitle("Distribution of Maths scores")
knitr::opts_chunk$set(warning = FALSE)
Code 
p2 <- ggplot(data=exam_data, 
             aes(x = ENGLISH)) +
  geom_histogram(bins=20, 
                 boundary = 100,
                 color="grey25", 
                 fill="black") +
  coord_cartesian(xlim=c(0,100)) +
  ggtitle("Distribution of English scores")
knitr::opts_chunk$set(warning = FALSE)
Code 
p3 <- ggplot(data=exam_data, 
             aes(x= MATHS, 
                 y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, 
              size=0.5) +  
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100)) +
  ggtitle("English scores versus Maths scores for Primary 3")
knitr::opts_chunk$set(warning = FALSE)

Patchwork is a ggplot2 extension designed to combine separate ggplot2 graphs into a single figure. Here’s the syntax.

  • “/” operator to stack two ggplot2 graphs

  • “|” operator to place the plots beside each other

  • “()” operator the define the sequence of the plotting

Code 
p1 + p2

Code 
(p1 / p2) | p3

Code 
patchwork <- (p1 / p2) | p3
patchwork

Code 
p3 <- ggplot(data=exam_data, 
             aes(x= MATHS, 
                 y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, 
              size=0.5) +  
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100)) +
  ggtitle(stringr::str_wrap("English scores versus Maths scores for Primary 3", width = 30)) +
  theme_wsj() +
  theme(plot.title = element_text(hjust = 0.5, size = 15, face = "bold"))