# Cut Off Highest Values from ggplot2 Plot in R (2 Examples)

In this R tutorial you’ll learn how to display only the lower 95% of a density or histogram.

So now the part you have been waiting for – the examples:

## Creation of Example Data

The first step is to create some example data:

```set.seed(357948)                                      # Create example data
data <- data.frame(x = rnorm(250)) Table 1 shows the head of our example data – Furthermore, it gets visible that our data is constituted of one variable with the names “x”.

## Example 1: Add 95% Line to ggplot2 Plot

The following R syntax demonstrates how to draw a red line at the 95% highest value to a graph.

For this, we first need to define the value of this cut-off point:

```cut_95 <- sort(data\$x)[round(length(data\$x) * 0.95)]  # Create cut-off value
cut_95                                                # Print cut-off value
#  1.667292```

Based on the previous calculation we can see that 95% of our values are below the cut-off value 1.667292, and 5% are larger than this value.

Next, we can visualize this cut-off value as a red line to a graphic.

In this example, we use the ggplot2 package to draw our data. We first have to install and load the ggplot2 package, in order to use the corresponding functions and commands:

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

Next, we can use the following R code to draw our data. Note that we are using the geom_vline function to add a vertical red line to our ggplot2 plot.

```ggplot(data, aes(x)) +                                # Draw density with 95% line
geom_density() +
geom_vline(xintercept = cut_95, col = "red")``` The output of the previous syntax is illustrated in Figure 1: We have created a ggplot2 density plot with a red line indicating the 95% cut-off that we have computed before.

We can use basically the same R code to draw our data in a histogram. All we have to do is to exchange the geom_density function by the geom_histogram function:

```ggplot(data, aes(x)) +                                # Draw histogram with 95% line
geom_histogram() +
geom_vline(xintercept = cut_95, col = "red")``` As shown in Figure 2, we have created a ggplot2 histogram with a vertical line at the 95% cut-off value.

## Example 2: Remove Highest 5% of Values from ggplot2 Plot

In Example 1, we have drawn a red line at our cut-off value. Example 2 explains how to remove all values on the right side of our cut-off line entirely.

For this, we first have to create a data frame subset that contains only the lower 95% of our values:

`data_95 <- data[data\$x <= cut_95, , drop = FALSE]     # Remove highest 5%`

Next, we can draw the lower 95% of our data in a density:

```ggplot(data_95, aes(x)) +                             # Draw density of lower 95%
geom_density()``` Alternatively, we could draw our data frame subset in a histogram:

```ggplot(data_95, aes(x)) +                             # Draw histogram of lower 95%
geom_histogram()``` ## Video, Further Resources & Summary

If you need further information on the R programming code of this article, you might have a look at the following video on my YouTube channel. In the video, I’m explaining the R programming syntax of this article.

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Furthermore, you may want to read the other articles of my homepage. You can find some tutorials on topics such as groups, labels, and ggplot2 below.

Summary: You have learned in this tutorial how to show only the x highest or lowest values in a ggplot2 graphic in the R programming language. If you have additional comments or questions, please let me know in the comments.

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• Dr.Duleep Kumar Samuel
June 7, 2021 3:01 pm

The code makes me so happy and it is a joy to read and practice, it will be nice if all the articles and videos are made available as a large single zip file. thanks. You can write a great book on R

• June 8, 2021 5:46 am

Hey Duleep,

Thanks a lot for this awesome feedback, glad to hear that you enjoy reading my tutorials!

I have not planned to make the content available as zip-file (this would be a HUGE file), but you can always access it for free on the website and the YouTube channel.

Regards

Joachim