Combining plots in R

In R Programming Language, you can combine plots using ‘par’ function. Combining plots will help you to make decisions easily. Comparing results will be easy by combining plots. par() function is used to set the parameters for multiple plots, and the layout() function determines how the plots should be arranged. To combine different plots first individual plots should be created, you can use the plot() and legend() functions to add every single plot to a single plotting window.

Why do you have to combine plots?

While performing data analysis there may be a situation where we need to compare both plots and make decisions according to them. Data analysts combine plots to look at different plots at the same time.

Parameters in par() function

Parameter	Description
mfrow()	used to specify the plots row-wise
mfcol()	used to specify the plots column wise
layout()	It takes a matrix as its argument, where each element of the matrix represents a plotting region in the layout

Using mfrow to combine plots

We will use the palmerpenguins data set for a while. In this example, we create two single plots and combine them row-wise using the par() function and mfrow parameter.

R

#install palmerpenguins package
install.packages("palmerpenguins")
library(palmerpenguins)

# combined plot with 2 rows and 1 column
par(mfrows = c(2,1))

# first single plot
plot(penguins$body_mass_g,
     penguins$flipper_length_mm,
     main = "ScatterPlot",
     xlab = "body_mass",
     ylab = "flipper_length")

# second single plot
plot(penguins$bill_depth_mm,
     penguins$bill_length_mm,
     main = "ScatterPlot",
     xlab = "bill_depth",
     ylab = "bill_length")

Output:

combined plots using mfrows

Using mfcol to combine plots

In this example, we create two single plots and combine them column-wise using par() method and mfcol parameter.

R

#create data
math_marks <- c(90, 95, 85, 76, 65)
science_marks <- c(45, 98, 54, 87, 65)
student_names <- c("A", "B", "C", "D", "E")

# combine plots with 1 row and 2 columns
par(mfcol = c(1,2))

# first pie chart
pie(math_marks, student_names,
    main = "PieChart", radius = 0.75)

# second pie chart
pie(science_marks, student_names,
    main = "Piechart", radius = 0.75)

Output:

combined pie charts using mfcol

Using layout() to combine plots

We use the layout() parameter to combine plots according to our requirements and we use layout() to customize the combined plot. 

Note: layout() function can be used only within an open device, otherwise you will get an error.

To avoid errors while using layout() function use the windows() function which creates a new window to combine plots.layout() takes a matrix as its arguments along with nrow and ncol etc.

R

game <- data.frame(scores <- c(34, 54, 21, 67, 98),
                   players <- c("A", "B", "C", "D", "E"),
                   avg_score <- c(56, 43, 65, 23, 16))
# display plot on screen
windows()

# create layout
layout(matrix(c(1, 2, 3, 4), nrow = 2,
              ncol = 2, byrow = TRUE))

# first plot
plot(game$scores, game$avg_score,
     main = "ScatterPlot",
     xlab = "Score_in_game",
     ylab = "avg_score")

# second plot
boxplot(game$avg_score, main = "Boxplot")

# third plot
hist(game$scores, main = "Histogram",
     xlab = "scores")

# fourth plot
pie(game$avg_score, game$players,
    main = "Piechart", radius = 0.75)

Output:

combined plots using layout()

To display the layout of the plot, you can use layout.show() function. More examples of layout() function

R

par(mfrow = c(2, 2), mar=c(5, 5, 5, 5))
layout(matrix(c(2, 0, 1, 3), 2, 2, byrow = TRUE),
       widths=c(3, 3), heights=c(1, 3))

# Create sample data
set.seed(123)
x <- rnorm(100)
y <- rnorm(100)

# Create barplot
barplot(x, main = "Bar Plot", col = "blue")

# Create scatterplot
plot(x, y, main = "Scatter Plot",
     col = "red", pch = 16)

# Create densityplot
d <- density(x)
plot(d, main = "Density Plot",
     col = "green", type = "l")

Output:

combined plots using layout()

R

layout(matrix(c(1,2,3,3), ncol=2, byrow=TRUE))
x <- rnorm(100)
y <- rnorm(100)
plot(density(x), col = "green")
plot(x, y, 'p', col = "red")
barplot(x, col = "yellow")

Output:

combined plots using layout()

We can create just a simple layout without any graphs in it for demonstration purposes.

R

example <- layout(matrix(c(2, 0, 1, 3),
                         2, 2, byrow = TRUE))
# display layout
layout.show(example)

Output: