Hands_on_ex1

##Step 1: Installing the required libraries

pacman::p_load(tidyverse)

Importing the required data

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

##Step 2: View the data in histogram

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")

##Step 3: Essential Grammatical Elements in ggplot2 with Aesthetic Mapping

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

Visualising data in Histogram

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

Visualising data in Dotplot

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

Visualising data in Histogram in bins

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

Adding colors

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

Visualising data with data plotlines - geomdensity()

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

Visualising data with Boxplot diagrams

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

Visualising data with violin plot - geomviolin()

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

Visualising data in scatterplot

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

Combining boxplot with scatter plot

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

Working with Essential Grammatical Elements in ggplot2: stat

Working with stat summary

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

Overriding soothing methods

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

Working with Essential Grammatical Elements in ggplot2: Facet

Using Facetwraps

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

Using Facet Grid

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