Hands-on Exercise 1

1. Getting Started

Install and launching R packages.

The code chunk below uses p_load() of pacman package to check if tidyverse packages are installed in the computer. If they are, then they will be launched into R.

pacman::p_load(tidyverse)

Importing the data

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

2. Try-It-Yourself Exercise

Working with facet

Example 1 Plotting trellis boxplot using facet_wrap by GENDER

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

Example 2 Plotting trellis boxplot using facet_grid by GENDER

ggplot(data = exam_data,
       aes(x = CLASS,
           y = MATHS)) +
  geom_boxplot() +
  facet_grid(GENDER ~ .)

Example 3 Plotting 2-D trellis boxplot using facet_grid

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

Working with theme

Example 4 Changing theme of bar plot

ggplot(data=exam_data, 
       aes(x=RACE)) +
  geom_bar() +
  coord_flip() +
  theme(panel.background = element_rect(fill = "light blue"),
        panel.grid = element_line(color = "white"))

Designing Data-driven Graphics for Analysis

Exercise 1

ggplot(data=exam_data, 
       aes(x = fct_infreq(RACE))) +
  geom_bar() +
  geom_text(stat = "count", 
            aes(label = paste0(after_stat(count), ", ",
                        round(after_stat(count)/sum(after_stat(count))*100,
                        1), "%")), 
            vjust = -1) +
  labs(
    x = "Race",
    y = "No. of\nPupils") +
  theme(axis.title.y = element_text(angle = 0))

Exercise 2

ggplot(data = exam_data,
       aes(x = MATHS)) +
  geom_histogram(bins = 20,
                 color = "black",
                 fill = "light blue") +
  geom_vline(aes(xintercept = mean(MATHS)),
             linetype = "dashed",
             color = "red") +
  geom_vline(aes(xintercept = median(MATHS)),
             linetype = "dashed",
             color = "black")

Exercise 3

ggplot(data = exam_data,
       aes(x = ENGLISH)) +
  geom_histogram(data = exam_data |> select(ENGLISH), 
                 bins = 30,
                 alpha = 0.3) +
  geom_histogram(aes(fill = GENDER),
                 bins = 30,
                 color = "black",
                 show.legend = FALSE) +
  facet_grid(~ GENDER) +
  theme_bw()

Exercise 4

ggplot(data = exam_data,
       aes(y = ENGLISH,
           x = MATHS)) +
  geom_point() +
  coord_cartesian(xlim = c(0,100),
                  ylim = c(0,100)) +
  geom_vline(aes(xintercept = 50),
             linetype = "dashed",
             color = "grey40") +
  geom_hline(aes(yintercept = 50),
             linetype = "dashed",
             color = "grey40")