Hands-on Exercise 1

Author

Zachary Wong

Published

January 7, 2024

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
Additional code to check on data

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

summary(exam_data)

      ID               CLASS              GENDER              RACE          
 Length:322         Length:322         Length:322         Length:322        
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
    ENGLISH          MATHS          SCIENCE     
 Min.   :21.00   Min.   : 9.00   Min.   :15.00  
 1st Qu.:59.00   1st Qu.:58.00   1st Qu.:49.25  
 Median :70.00   Median :74.00   Median :65.00  
 Mean   :67.18   Mean   :69.33   Mean   :61.16  
 3rd Qu.:78.00   3rd Qu.:85.00   3rd Qu.:74.75  
 Max.   :96.00   Max.   :99.00   Max.   :96.00

Plotting a simple bar chart

Using GGplot2 (Histogram)

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

Using GGplot2 (Dotplot)

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

Modifying A Geometric Object by Changing aes()

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

Geometric Objects: geom-density()

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

Geometric Objects: `geom_boxplot`

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

Warning in geom_boxplot(notches = TRUE): Ignoring unknown parameters: `notches`

Geometric Objects: geom_violin

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

Geometric Objects: geom_point()

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

Combining geom Objects

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

Warning: Continuous x aesthetic
ℹ did you forget `aes(group = ...)`?

Adding Essential Grammatical Elements in ggplot2: stat

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

Warning: The `fun.y` argument of `stat_summary()` is deprecated as of ggplot2 3.3.0.
ℹ Please use the `fun` argument instead.

Adding a Best Fit Curve on a Scatterplot

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

Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
ℹ Please use `linewidth` instead.

`geom_smooth()` using formula = 'y ~ x'

Adding Essential Grammatical Elements in ggplot2: Facets

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

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

Essential Grammatical Elements in ggplot2: Coordinates

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

Changing the y- and x-axis Range

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))

`geom_smooth()` using formula = 'y ~ x'

Essential Grammatical Elements in ggplot2: Themes

Gray Theme

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

Classic Theme

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

Classic Minimal

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