How exactly are outliers removed in R boxplot and how can the same outliers be removed for further calculation (e.g. mean)?

Question

In a boxplot I've set the option outline=FALSE to remove the outliers.
Now I'd like to include points that show the mean in the boxplot. Obviously, the means calculated using mean include the outliers.

How can the very same outliers be removed from a dataframe so that the calculated mean corresponds to the data shown in the boxplot?

I know how outliers can be removed, but which settings are used by the outline option from boxplot internally? Unfortunately, the manual does not give any clarifications.

Answer 1

To remove the outliers, you must set the option outline to FALSE.

Let's assume that your data are the following:

data <- data.frame(a = c(seq(0,1,0.1),3))

Then, you use the boxplot function:

res <- boxplot(data, outline=FALSE)

In the res object, you have several pieces of information about your data. Among these, res$out gives you all the outliers. Here there is only the value 3.

Thus, to compute the mean without the outliers, you can simply do:

mean(data$a[!data$a %in% res$out])