Introduction to Greek Letters in R Plot
The post is about writing Greek letters in R plot, their labels, and the title of the plots. There are two main ways to include Greek letters in your R plot labels (axis labels, title, legend):
- Using the
expressionFunction
This is the recommended approach as it provides more flexibility and control over the formatting of the Greek letters and mathematical expressions. - Using raw Greek letter Codes
This method is less common and requires memorizing the character codes for each Greek letter.
Table of Contents
Question: How one can include Greek letters (symbols) in R plot labels?
Answer: Greek letters or symbols can be included in titles and labels of a graph using the expression command. Following are some examples
Note that in these examples random data is generated from a normal distribution. You can use your own data set to produce graphs that have symbols or Greek letters in their labels or titles.
Greek Letters in R Plot
The following are a few examples of writing Greek letters in R plot.
Example 1: Draw Histogram
mycoef <- rnorm (1000) hist(mycoef, main = expression(beta) )
where beta in expression is the Greek letter (symbol) of $latex \beta$. A histogram similar to the following will be produced.
Example 2:
sample <- rnorm(mean=5, sd=1, n=100)
hist(sample, main=expression( paste("sampled values, ", mu, "=5, ", sigma, "=1" )))where mu and sigma are symbols of $latex \mu$ and $latex \sigma$ respectively. The histogram will look like
Example 3:
curve(dnorm, from= -3, to=3, n=1000, main="Normal Probability Density Function")
will produce a curve of Normal probability density function ranging from $latex -3$ to $latex 3$.
Normal Density Function
To add a normal density function formula, we need to use the text and paste command, that is
text(-2, 0.3, expression(f(x) == paste(frac(1, sqrt(2*pi* sigma^2 ) ), " ", e^{frac(-(x-mu)^2, 2*sigma^2)})), cex=1.2)Now the updated curve of the Normal probability density function will be
Example 4:
x <- dnorm( seq(-3, 3, 0.001))
plot(seq(-3, 3, 0.001), cumsum(x)/sum(x),
type="l", col="blue", xlab="x",
main="Normal Cumulative Distribution Function")The Normal Cumulative Distribution function will look like,
To add the formula, use the text and paste command, that is
text(-1.5, 0.7,
expression(phi(x) == paste(frac(1, sqrt(2*pi)), " ",
integral(e^(-t^2/2)*dt, -infinity, x))), cex = 1.2)The curve of Normal Cumulative Distribution Function
The Curve of the Normal Cumulative Distribution Function and its formula in the plot will look like this,
