Overlay Histogram with Fitted Density Curve in Base R & ggplot2 Package (2 Examples)

In this tutorial you’ll learn how to fit a density plot to a histogram in the R programming language.

Table of contents:

• Introduction of Example Data
• Example 1: Histogram & Density with Base R
• Example 2: Histogram & Density with ggplot2 Package
• Video, Further Resources & Summary

Let’s just jump right in!

Introduction of Example Data

In the examples of this R programming tutorial, we’ll use the following example data:

set.seed(18462)                                       # Create example data
data <- data.frame(x = round(rnorm(1000, 10, 10)))
head(data)                                            # Print example data
#     x
# 1   6
# 2   7
# 3  14
# 4   4
# 5 -10
# 6  16

As you can see based on the output of the RStudio console, our example data contains only one numeric column. Now, let’s draw these data…

Example 1: Histogram & Density with Base R

Example 1 explains how to fit a density curve to a histogram with the basic installation of the R programming language. First, we need to use the hist function to draw a histogram:

hist(data$x, prob = TRUE)                             # Create histogram with Base R

Figure 1: Histogram Created with Base R.

Figure 1 shows the output of the previous R code: A histogram without a density line. If we want to add a kernel density to this graph, we can use a combination of the lines and density functions:

lines(density(data$x), col = "red")                   # Overlay density curve

Figure 2: Histogram & Overlaid Density Plot Created with Base R.

Figure 2 illustrates the final result of Example 1: A histogram with a fitted density curve created in Base R.

Example 2: Histogram & Density with ggplot2 Package

Example 2 shows how to create a histogram with a fitted density plot based on the ggplot2 add-on package. First, we need to install and load ggplot2 to R:

install.packages("ggplot2")                           # Install & load ggplot2
library("ggplot2")

Now, we can use a combination of the ggplot, geom_histogram, and geom_density functions to create out graphic:

ggplot(data, aes(x)) +                                # ggplot2 histogram & density
  geom_histogram(aes(y = stat(density))) +
  geom_density(col = "red")

Figure 3: Histogram & Overlaid Density Plot Created with ggplot2 Package.

Figure 3 visualizes our histogram and density line created with the ggplot2 package. Note that the histogram bars of Example 1 and Example 2 look slightly different, since by default the ggplot2 packages uses a different width of the bars compared to Base R.

Video, Further Resources & Summary

Some time ago I have published a video on my YouTube channel, which illustrates the content of this tutorial. You can find the video below:

Furthermore, you might want to have a look at some of the related articles which I have published on my homepage.

• Create Histogram in Base R
• Create Kernel Density Plot in R
• Create ggplot2 Histogram in R
• Draw Multiple Overlaid Histograms with ggplot2 Package
• Draw Multiple Variables as Lines to Same ggplot2 Plot
• R Graphics Gallery
• The R Programming Language

In this tutorial, I illustrated how to combine histograms with probability on the y-axis and density plots in the R programming language. If you have additional questions or comments, let me know in the comments section below.