Plot Barchart with ggplot2 in R

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Barcharts can be used to plot the frequency of a single categorical variable, or illustrate the cross relationship between two or more categorical variables. In R programming, function geom_bar() from ggplot2 package can easily create simple barcharts, stacked or grouped barcharts. The following codes show creation of different barcharts, using a virtual dataset “grade”.

1. Create data frame ‘grade’ by reading csv file from working directory.

#set the number of digits printed
options(digits = 2)  
 # to set working directory
setwd("d:\\RStatistics-Tutorial")  
#create a grade data frame
vartype<-c("character", "character", "character", "character", "character", "numeric","numeric", "numeric","numeric","character")
grade <- read.table("University-Fullname-full.csv", colClasses=vartype, header=TRUE, sep=",")                                      

#to show first several observations of the data frame
head(grade)
  StudentID        Fullname Race Gender Country Age Math Physics
1         1     James Zhang    A   Male      US  23   73      70
2         2       Wilson Li    E Female      UK  26   95      76
3         3 Richard Nuan Ye    A   Male      UK  35   77      83
4         4       Mary Deng    E Female      US  21   60      99
5         5    Jason Wilson    A   Male      UK  19   77      89
6         6 Jennifer Hopkin    A Female      UK  43   79      64
  Chemistry       Date
1        87 10/31/2008
2        83  3/16/2008
3        92  5/22/2008
4        84  1/24/2009
5        93  7/30/2009
6        83   4/5/2009

2. Create a simple vertical barchart

#Simple vertical bar chart of variable 'Gender'
ggplot(grade, aes(x=Gender)) + geom_bar() +
  labs(title="Simple Bar chart",                 
       x="Gender",                          
       y="Frequency") 

        

3. We can also plot a simple horizontal barchart using the same variable

#Simple horizontal bar chart
ggplot(grade, aes(x=Gender)) + geom_bar() +
  labs(title="Horizontal Bar chart",             
       x="Gender",                          
       y="Frequency") +                          
  coord_flip()  

4. If we want to show how is the variation of one categorical variable inside another categorical variable, then stacked or group barcharts are appropriate. The following code is used for creating a stacked barchart, where different countries are stacked together inside each Gender value.

ggplot(grade, aes(x=Gender, fill=Country)) +
  geom_bar(position = "stack") +  
  labs(title="Stacked Bar chart",                   
       x="Gender",                               
       y="Country") 

5. Comparatively, categorical variables can be grouped alongside when we plot barcharts to reflect cross relationship between two variables. Here, a grouped barchart is plotted in which countries values stay side by side with each Gender value.

ggplot(grade, aes(x=Gender, fill=Country)) +
  geom_bar(position = "dodge") + 
  labs(title="Grouped Bar chart",                   
       x="Gender",                               
       y="Country")   

6. Another type barchart is filled barchart. It is quite similar as stacked barchart, while the hight of each bar is scaled to same length, such that the proportion of the categorical variable inside could be identified by first glance.

ggplot(grade, aes(x=Gender, fill=Country)) +
  geom_bar(position = "fill") +  
  labs(title="Filled Bar chart",                   
       x="Gender",                               
       y="Country") 

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