# Plot outliers and their values

[This article was first published on

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

**modTools**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

The ‘*plot_outliers*‘ function below draws a **boxplot **and a **scatterplot **of a numeric variable *x* and plots the **values of the outliers** (currently not offset, even if they overlap). For relatively small datasets, it can be a quick way to identify which outliers look reasonable and which are likely a result of transcription or measurement error, and thus should be either corrected or discarded.

```
plot_outliers <- function(x, val_col = "blue", ...) {
par_in <- par(no.readonly = TRUE)
par(mfrow = c(1, 2))
bp <- boxplot(x, ...)
out <- bp$out
message(length(out), " outliers detected")
if (length(out) > 0) text(x = 0.5, y = bp$out, labels = round(out, 2), adj = 0, col = val_col)
plot(x, pch = 20)
if (length(out) > 0) text(x = 0.5, y = bp$out, labels = round(out, 2), adj = 0, col = val_col)
par(par_in)
}
```

**Usage examples:**

`plot_outliers(iris$Sepal.Width)`

Additional arguments for the ‘*boxplot*‘ function can be provided, e.g.

`plot_outliers(airquality$Ozone, notch = TRUE)`

`plot_outliers(airquality$Wind, col = "darkgreen", main = "wind")`

This function is used in an article which we hope to submit soon.

To

**leave a comment**for the author, please follow the link and comment on their blog:**modTools**.R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.