# Overlay Normal Density Curve on Top of ggplot2 Histogram in R (Example)

In this R tutorial youâ€™ll learn how to **draw a ggplot2 histogram and a normal density line in the same graph**.

The tutorial will consist of one example for the plotting of histograms and normal curves. To be more precise, the tutorial contains this content:

Letâ€™s start right away:

## Example Data, Packages & Default Plot

To start with, we need to construct some data that we can use in the following examples:

set.seed(119864293) # Create example data data <- data.frame(x = rnorm(300)) head(data) # Print head of example data |

set.seed(119864293) # Create example data data <- data.frame(x = rnorm(300)) head(data) # Print head of example data

Have a look at the table that got returned after executing the previous R programming syntax. It shows that our example data has 300 observations and one column.

If we want to plot the data using the ggplot2 add-on package, we also have to install and load ggplot2:

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

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

Next, we can create a plot of the data using the ggplot2 package:

ggplot(data, aes(x)) + # Draw regular histogram without density geom_histogram() |

ggplot(data, aes(x)) + # Draw regular histogram without density geom_histogram()

As shown in Figure 1, we have created a ggplot2 histogram with default specifications and without a normal density curve on top.

## Example: Add Normal Density Curve to ggplot2 Histogram Using stat_function()

This example explains how to create a ggplot2 histogram with overlaid normal density curve.

First, we have to convert the y-axis values of our histogram to probabilities. Otherwise, our density curve will not be shown properly.

Have a look at the following R code and the resulting graphic:

ggplot(data, aes(x)) + # Draw histogram with probabilities geom_histogram(aes(y = ..density..)) |

ggplot(data, aes(x)) + # Draw histogram with probabilities geom_histogram(aes(y = ..density..))

Figure 2 shows the output of the previous code: A ggplot histogram with probabilities on the y-axis. However, thereâ€™s still no normal density line in the plotâ€¦

We can add such a normal density curve to our plot using the stat_function command as shown below:

ggplot(data, aes(x)) + # Draw histogram with density geom_histogram(aes(y = ..density..)) + stat_function(fun = dnorm, args = list(mean = mean(data$x), sd = sd(data$x)), col = "#1b98e0", size = 5) |

ggplot(data, aes(x)) + # Draw histogram with density geom_histogram(aes(y = ..density..)) + stat_function(fun = dnorm, args = list(mean = mean(data$x), sd = sd(data$x)), col = "#1b98e0", size = 5)

After running the previous R syntax the ggplot2 histogram with normal density curve shown in Figure 3 has been drawn.

Looks great!

## Video, Further Resources & Summary

Do you want to know more about ggplot2 graphics? Then you may watch the following video of my YouTube channel. Iâ€™m illustrating the topics of this article in the video.

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In addition, you may have a look at some of the related articles on this homepage.

- Create ggplot2 Histogram in R
- Plot Frequencies on Top of Stacked Bar Chart with ggplot2
- Add Image to Plot in R
- Add Count Labels on Top of ggplot2 Barchart
- Overlay Histogram with Fitted Density Curve in Base R & ggplot2 Package
- Graphics Gallery in R
- The R Programming Language

Summary: In this R tutorial you have learned how to **overlay a normal distribution line on top of a ggplot2 histogram**. Tell me about it in the comments below, in case you have further questions.

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