Hands-on_Exercise1

Author

Ho Tung

Published

January 10, 2026

Modified

January 17, 2026

1.1 Overview

Basic principles and essential components of ggplot2

1.2 Getting started

pacman::p_load(tidyverse)

1.2.2 Importing data

exam_data <- read_csv("data/Exam_data.csv")

1.3 Introducing ggplot

1.3.1 R Graphics VS ggplot

hist(exam_data$MATHS)

ggplot(data=exam_data, aes(x = MATHS)) +
  geom_histogram(bins=10, 
                 boundary = 100,
                 color="black", 
                 fill="grey") +
  ggtitle("Distribution of Maths scores")

1.4 Grammar of Graphics

1.4.1 A Layered Grammar of Graphics

1.5 Essential Grammatical Elements in ggplot2: data

ggplot(data=exam_data)

1.6 Essential Grammatical Elements in ggplot2: Aesthetic mappings

ggplot(data=exam_data, 
       aes(x= MATHS))

1.7 Essential Grammatical Elements in ggplot2: geom 1.7.1 Geometric Objects: geom_bar

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar()

1.7.2 Geometric Objects: geom_dotplot

ggplot(data=exam_data, 
       aes(x = MATHS)) +
  geom_dotplot(dotsize = 0.5)

ggplot(data=exam_data, 
       aes(x = MATHS)) +
  geom_dotplot(binwidth=2.5,         
               dotsize = 0.5) +      
  scale_y_continuous(NULL,           
                     breaks = NULL)

1.7.3 Geometric Objects: geom_histogram()

ggplot(data=exam_data, 
       aes(x = MATHS)) +
  geom_histogram()

1.7.4 Modifying a geometric object by changing geom()

ggplot(data=exam_data, 
       aes(x= MATHS)) +
  geom_histogram(bins=20,            
                 color="black",      
                 fill="light blue")

1.7.5 Modifying a geometric object by changing aes()

ggplot(data=exam_data, 
       aes(x= MATHS, 
           fill = GENDER)) +
  geom_histogram(bins=20, 
                 color="grey30")

1.7.6 Geometric Objects: geom-density()

ggplot(data=exam_data, 
       aes(x = MATHS)) +
  geom_density()           

ggplot(data=exam_data, 
       aes(x = MATHS, 
           colour = GENDER)) +
  geom_density()

1.7.7 Geometric Objects: geom_boxplot

ggplot(data=exam_data,
       aes(y = MATHS,       
           x= GENDER)) +    
  geom_boxplot()             

ggplot(data=exam_data, 
       aes(y = MATHS, 
           x= GENDER)) +
  geom_boxplot(notch=TRUE)

1.7.8 Geometric Objects: geom_violin

ggplot(data=exam_data, 
       aes(y = MATHS, 
           x= GENDER)) +
  geom_violin()

1.7.9 Geometric Objects: geom_point()

geom_point()

ggplot(data=exam_data, 
       aes(x= MATHS, 
           y=ENGLISH)) +
  geom_point()

1.7.10 geom objects can be combined

ggplot(data=exam_data, 
       aes(y = MATHS, 
           x= GENDER)) +
  geom_boxplot() +                    
  geom_point(position="jitter", 
             linewidth = 0.5)

1.8 Essential Grammatical Elements in ggplot2: stat

1.8.1 Working with stat()

ggplot(data=exam_data, 
       aes(y = MATHS, x= GENDER)) +
  geom_boxplot()

1.8.2 Working with stat - the stat_summary() method

stat_summary() function

ggplot(data=exam_data, 
       aes(y = MATHS, x= GENDER)) +
  geom_boxplot()

1.8.2 Working with stat - the stat_summary() method stat_summary() 

ggplot(data=exam_data, 
       aes(y = MATHS, x= GENDER)) +
  geom_boxplot() +
  stat_summary(geom = "point",       
               fun = "mean",         
               colour ="red",        
               linewidth=4)

1.8.3 Working with stat - the geom() method

ggplot(data=exam_data, 
       aes(y = MATHS, x= GENDER)) +
  geom_boxplot() +
  geom_point(stat="summary",        
             fun="mean",           
             colour="red",          
             linewidth=4)

1.8.4 Adding a best fit curve on a scatterplot?

geom_smooth() 

ggplot(data=exam_data, 
       aes(x= MATHS, y=ENGLISH)) +
  geom_point() +
  geom_smooth(linewidth=0.5)

ggplot(data=exam_data, 
       aes(x= MATHS, 
           y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, 
              linewidth=0.5)

1.9 Essential Grammatical Elements in ggplot2: Facets

facet_grid() and facet_wrap

1.9.1 Working with facet_wrap()

ggplot(data=exam_data, 
       aes(x= MATHS)) +
  geom_histogram(bins=20) +
    facet_wrap(~ CLASS)

1.9.2 facet_grid() function

ggplot(data=exam_data, 
       aes(x= MATHS)) +
  geom_histogram(bins=20) +
    facet_grid(~ CLASS)

1.10 Essential Grammatical Elements in ggplot2: Coordinates

- [`coord_cartesian()`](https://ggplot2.tidyverse.org/reference/coord_cartesian.html): the default cartesian coordinate systems, where you specify x and y values (e.g. allows you to zoom in or out). - [`coord_flip()`](https://ggplot2.tidyverse.org/reference/coord_flip.html): a cartesian system with the x and y flipped. - [`coord_fixed()`](https://ggplot2.tidyverse.org/reference/coord_fixed.html): a cartesian system with a “fixed” aspect ratio (e.g. 1.78 for a “widescreen” plot). - [`coord_quickmap()`](https://ggplot2.tidyverse.org/reference/coord_map.html): a coordinate system that approximates a good aspect ratio for maps.


1.10.1 Working with Coordinate

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar()

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar() +
  coord_flip()

1.10.2 Changing the y- and x-axis range

ggplot(data=exam_data, 
       aes(x= MATHS, y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, linewidth=0.5)

ggplot(data=exam_data, 
       aes(x= MATHS, y=ENGLISH)) +
  geom_point() +
  geom_smooth(method=lm, 
              linewidth=0.5) +  
  coord_cartesian(xlim=c(0,100),
                  ylim=c(0,100))

1.11 Essential Grammatical Elements in ggplot2: themes

1.11.1 Working with theme

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar() +
  coord_flip() +
  theme_gray()

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar() +
  coord_flip() +
  theme_classic()

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar() +
  coord_flip() +
  theme_classic()

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar() +
  coord_flip() +
  theme_classic()

1.12 Reference