Fit Smooth Curve to Plot of Data in R (Example)

In this tutorial you’ll learn how to draw a smooth line to a scatterplot in the R programming language.

Table of contents:

Here’s how to do it:

Introduction of Example Data

The following data is used as basement for this R programming tutorial:

set.seed(87564832)              # Create example data
x <- 1:100
y <- sort(rnorm(100))

The previous output of the RStudio console shows the structure of our example data. It consists of two numeric vectors each containing 100 values.

Now, we can draw our data as follows:

plot(x, y)                      # Plot without line

Figure 1 visualizes the output of the previous R syntax: A scatterplot showing our data. However, this scatterplot does not show a fitted curve yet…

Example: Creating Scatterplot with Fitted Smooth Line

The following R code explains how to draw a fitted curve to our example plot. Have a look at the following R code:

curve_values <- loess(y ~ x)    # Apply loess function

plot(x, y)                      # Plot with line
lines(predict(curve_values),
      col = "red",
      lwd = 3)

As shown in Figure 2, we created a scatterplot with a fitted curve with the previous R code.

Video & Further Resources

Do you want to learn more about smooth curves in graphics? Then I can recommend to watch the following video of my YouTube channel. In the video, I’m explaining the topics of this article:

The YouTube video will be added soon.

Furthermore, you may have a look at the related R tutorials of my website. Some posts are shown below.

• The lowess() R Smoothing Function
• Overlay Histogram with Fitted Density Curve in Base R & ggplot2 Package
• The R Programming Language

Summary: You learned in this article how to add a smooth curve to a plot in the R programming language. In case you have further questions or comments, let me know in the comments section below. Furthermore, don’t forget to subscribe to my email newsletter to receive updates on new articles.