Installing and Loading All required libraries

packages <- c('tinytex','RColorBrewer','classInt','ggthemes','tidyverse')

for (p in packages){
  if(!require(p,character.only =T)){
    install.packages(p)
  }
  library(p, character.only = T)
}

#Importing Data

The codes below import “exam_data.csv” into R environment using “read_csv()” function of readr package.

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

## Parsed with column specification:
## cols(
##   ID = col_character(),
##   CLASS = col_character(),
##   GENDER = col_character(),
##   RACE = col_character(),
##   ENGLISH = col_double(),
##   MATHS = col_double(),
##   SCIENCE = col_double()
## )

#Essential Grammartical Elements in ggplot2 ##The ggplot function

Let us call the ggplot() function using the code below. #Geometric Objects: geom_histogram

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

#Geometric Objects: geom_point & geom_boxplot

#error message will be prompted if visualization used is not appropriate #boxplot x axis uses categorical data #histogram uses numerical for x axis

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

#Geometric Objects: geom_dotplot

scale_y_continuous ( breaks =NULL) – removed the y axis

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

## Warning: Ignoring unknown parameters: size

#Working with facet_wrap()

“~” maps all the subgroups

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

#Working with facet_grid()

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

In-class Exercise

Installing and Loading All required libraries