Hands_On_Exercise 02

Author

Linn Thaw Tar

Installing Packages

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

Importing Data

exam_data <- read.csv('data/exam_data.csv')

Beyond ggplot2 Annotation: ggrepel

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('Eng Score vs Maths Score')

Using ggrepel to modify the graph above

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('Eng Score vs Maths Score')

ggplot2 themes

ggplot(data=exam_data, aes(x=MATHS))+ geom_histogram(bins=20,boundary=100,color='grey25',fill='grey90')+theme_minimal()+ggtitle('Distribution of Maths Score')

Working with hrbthems package

ggplot(data=exam_data, aes(x=MATHS)) + geom_histogram(bins=20,boundary=100,color="grey25", fill="grey90")+ggtitle('Distribution of Math')+theme_ipsum_es(axis_title_size = 18, base_size = 15, grid = "Y")

Creating Multiple Graphs

p1 <- ggplot(data=exam_data, aes(x=MATHS)) + geom_histogram(bins=20, boundary=100, color='grey25',fill='grey90')+coord_cartesian(xlim=c(0,100)) + ggtitle('Distribution of Maths Score')

p2 <- ggplot(data=exam_data, aes(x=ENGLISH)) + geom_histogram(bins=20, boundary=100, color='grey25',fill='grey90')+coord_cartesian(xlim=c(0,100)) + ggtitle('Distribution of ENGLISH Score')

p3 <- 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))+ggtitle('English vs Maths Score')

Combining Graphs

p1+p2

(p1/p2)|p3

((p1 / p2) | p3) + 
  plot_annotation(tag_levels = 'I')

Creating figure with insert

p3 + inset_element(p2, 
                   left = 0.02, 
                   bottom = 0.7, 
                   right = 0.5, 
                   top = 1)

Creating a composite figure by using patchwork and ggtheme

patchwork <- (p1 / p2) | p3
patchwork & theme_economist()