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R Programming : Bar Plot

Tutorial by:Maria Ghoste      Date: 2016-06-10 01:28:29

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Bar plots can be created in R using the barplot() function. We can supply a vector or matrix to this function. If we supply a vector, the plot will have bars with their heights equal to the elements in the vector. Let us suppose, we have a vector of maximum temperatures (in degree Celsius) for seven days as follows.

max.temp <- c(22, 27, 26, 24, 23, 26, 28)

Now we can make a bar plot out of this data.

barplot(max.temp)

R Programming Bar Plot

This function can take a lot of argument to control the way our data is plotted. You can read about them in the help section ?barplot. Some of the frequently used ones are, main to give the title, xlab and ylab to provide labels for the axes, names.arg for naming each bar, col to define color etc. We can also plot bars horizontally by providing the argument horiz=TRUE.

# barchart with added parameters

barplot(max.temp,
  main="Maximum Temperatures in a Week",
  xlab="Degree Celsius",
  ylab="Day",
  names.arg=c("Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat"),
  col="darkred",
  horiz=TRUE)

R Programming Bar Plot

Plotting Categorical Data

Sometimes we have to plot the count of each item as bar plots from categorical data. For example, here is a vector of age of 10 college freshmen.

age <- c(17,18,18,17,18,19,18,16,18,18)

Simply doing barplot(age) will not give us the required plot. It will plot 10 bars with height equal to the student's age. But we want to know the number of student in each age category. This count can be quickly found using the table() function, as shown below.

> table(age)
age
16 17 18 19 
1  2  6  1

Now plotting this data will give our required bar plot. Note below, that we define the argument density to shade the bars.

barplot(table(age),
  main="Age Count of 10 Students",
  xlab="Age",
  ylab="Count",
  border="red",
  col="blue",
  density=10
)

R Programming Bar Plot of Categorical Data

Plotting Higher Dimensional Tables

 

 
 

Sometimes the data is in the form of a contingency table. For example, let us take the built-in Titanic dataset. This data set provides information on the fate of passengers on the fatal maiden voyage of the ocean liner 'Titanic', summarized according to economic status (class), sex, age and survival.-R documentation.

> Titanic
, , Age = Child, Survived = No

     Sex
Class  Male Female
 1st     0      0
 2nd     0      0
 3rd    35     17
 Crew    0      0

, , Age = Adult, Survived = No

     Sex
Class  Male Female
 1st   118      4
 2nd   154     13
 3rd   387     89
 Crew  670      3

, , Age = Child, Survived = Yes

     Sex
Class  Male Female
 1st     5      1
 2nd    11     13
 3rd    13     14
 Crew    0      0

, , Age = Adult, Survived = Yes

     Sex
Class  Male Female
 1st    57    140
 2nd    14     80
 3rd    75     76
 Crew  192     20

We can see that this data has 4 dimensions, class, sex, age and survival. Suppose we wanted to bar plot the count of males and females. In this case we can use the margin.table() function. This function sums up the table entries according to the given index.

> margin.table(Titanic,1)  # count according to class
Class
1st  2nd  3rd Crew 
325  285  706  885 

> margin.table(Titanic,4)  # count according to survival
Survived
 No  Yes 
1490  711 

> margin.table(Titanic)  # gives total count if index is not provided
[1] 2201

Now that we have our data in the required format, we can plot, survival for example, as barplot(margin.table(Titanic,4)) or plot male vs female count as barplot(margin.table(Titanic,2)).

Plotting with Matrix

As mentioned before, barplot() function can take in vector as well as matrix. If the input is matrix, a stacked bar is plotted. Each column of the matrix will be represented by a stacked bar. Let us consider the following matrix which is derived from our Titanic dataset.

> titanic.data
       Class
Survival 1st 2nd 3rd Crew
    No  122 167 528  673
    Yes 203 118 178  212

This data is plotted as follows.

barplot(titanic.data,
  main="Survival of Each Class",
  xlab="Class",
  col=c("red","green")
)

legend("topleft",
  c("Not survived","Survived"),
  fill=c("red","green")
)

R Programming Stacked Bar Plot

We have used the function legend() to appropriately display the legend.

Instead of a stacked bar we can have different bars for each element in a column juxtaposed to each other by specifying the parameter beside=TRUE as shown below

R Programming Multiple Bar Plot

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R Programming

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