R Programming - Multiple Plots In One Graph

Hi there. In this post, the focus is on having multiple plots in one graph in the programming language R. The main R package that is used here is gridExtra. The main reference is http://lightonphiri.org/blog/ggplot2-multiple-plots-in-one-graph-using-gridextra. The original version of this post can be found on my website here.

A good reference for ggplot2 in R is the R Graphics Cookbook by Winston Chang.

Image Source

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Before entering in the main code, make sure to load in the ggplot2 and gridExtra packages into R. For installation of a R package use install.packages('pkg_name').

library(ggplot2)
library(gridExtra)

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Simulating Normal Random Variables Plot

For the first plot, I simulate 10000 standard normal random variables (mean of 0 and variance of 1) in R. Most of the values will lie within +3 standard deviations from the mean of 0. Values outside of 3 standard deviations are extreme cases or outliers.

The results are plotted in ggplot2 in the form of a histogram.

# Normals Plot:

normals <- rnorm(n = 10000, mean = 0, sd = 1)

norm_plot <- ggplot(data = NULL, aes(normals)) +
  geom_histogram(binwidth = 0.1, boundary = 2, col = "black", fill = "#D5ADA4") + 
  labs(x = "\n Number Of Standard Deviations (Z-Scores)", y = "Count \n", title = "Simulated Standard Normal Variates\n") +
  theme(plot.title = element_text(hjust = 0.5, size = 13, face = "bold", colour = "darkgreen"), 
        axis.title.x = element_text(face="bold", colour="#6f0000", size = 12),
        axis.title.y = element_text(face="bold", colour="#6f0000", size = 12))

# Show normals plot:
norm_plot

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Simulating Exponential Random Variables Plot

In the second plot, I simulate 10000 exponential random variables in R with the rexp() function with the rate of 3.

# Exponential Plot:

exponentials <- rexp(n = 10000, rate = 3)

exps_plot <- ggplot(data = NULL, aes(exponentials)) +
  geom_histogram(binwidth = 0.1, boundary = 2, col = "black", fill = "#b7b700") + 
  labs(x = "\n Value Of Exponential Random Variable", y = "Count \n", title = "Simulated Exponential Random Variables \n") +
  theme(plot.title = element_text(hjust = 0.5, size = 13, face = "bold", colour = "darkgreen"), 
        axis.title.x = element_text(face="bold", colour="#6f0000", size = 12),
        axis.title.y = element_text(face="bold", colour="#6f0000", size = 12))

# Show exponentials plot:
exps_plot

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Multiple Graphs In One With grid.arrange()

From the gridExtra package in R, multiple plots can be put into one graph with the use of the grid.arrange() function. I put both the normal and exponential random variables plot into one with ncol = 2.

# Two plots in one:
grid.arrange(norm_plot, exps_plot, ncol = 2)

Having plots side by side makes things easier for the viewer and is good for comparisons.