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)`

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)
```

## 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
)
```

## 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")
)
```

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