# Label line ends in time series with ggplot2

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@drsimonj here with a quick share on making great use of the secondary y axis with ggplot2 – super helpful if you’re plotting groups of time series!

Here’s an example of what I want to show you how to create (pay attention to the numbers of the right):

## Setup #

To setup we’ll need the tidyverse package and the `Orange`

data set that comes with R. This tracks the circumference growth of five orange trees over time.

library(tidyverse) d <- Orange head(d) #> Grouped Data: circumference ~ age | Tree #> Tree age circumference #> 1 1 118 30 #> 2 1 484 58 #> 3 1 664 87 #> 4 1 1004 115 #> 5 1 1231 120 #> 6 1 1372 142

## Template code #

To create the basic case where the numbers appear at the end of your time series lines, your code might look something like this:

# You have a data set with: # - GROUP colum # - X colum (say time) # - Y column (the values of interest) DATA_SET # Create a vector of the last (furthest right) y-axis values for each group DATA_SET_ENDS <- DATA_SET %>% group_by(GROUP) %>% top_n(1, X) %>% pull(Y) # Create plot with `sec.axis` ggplot(DATA_SET, aes(X, Y, color = GROUP)) + geom_line() + scale_x_continuous(expand = c(0, 0)) + scale_y_continuous(sec.axis = sec_axis(~ ., breaks = DATA_SET_ENDS))

## Let’s see it! #

Let’s break it down a bit. We already have our data set where the group colum is `Tree`

, the X value is `age`

, and the Y value is `circumference`

.

So first get a vector of the last (furthest right) values for each group:

d_ends <- d %>% group_by(Tree) %>% top_n(1, age) %>% pull(circumference) d_ends #> [1] 145 203 140 214 177

Next, let’s set up the basic plot without the numbers to see how each layer adds up.

ggplot(d, aes(age, circumference, color = Tree)) + geom_line()

Now we can use `scale_y_*`

, with the argument `sec.axis`

to create a second axis on the right, with numbers to be displayed at `breaks`

, defined by our vector of line ends:

ggplot(d, aes(age, circumference, color = Tree)) + geom_line() + scale_y_continuous(sec.axis = sec_axis(~ ., breaks = d_ends))

This is a great start, The only major addition I suggest is expanding the margins of the x-axis so the gap disappears. You do this with `scale_x_*`

and the `expand`

argument:

ggplot(d, aes(age, circumference, color = Tree)) + geom_line() + scale_y_continuous(sec.axis = sec_axis(~ ., breaks = d_ends)) + scale_x_continuous(expand = c(0, 0))

## Polishing it up #

Like it? Here’s the code to recreate the first polished plot:

library(tidyverse) d <- Orange %>% as_tibble() d_ends <- d %>% group_by(Tree) %>% top_n(1, age) %>% pull(circumference) d %>% ggplot(aes(age, circumference, color = Tree)) + geom_line(size = 2, alpha = .8) + theme_minimal() + scale_x_continuous(expand = c(0, 0)) + scale_y_continuous(sec.axis = sec_axis(~ ., breaks = d_ends)) + ggtitle("Orange trees getting bigger with age", subtitle = "Based on the Orange data set in R") + labs(x = "Days old", y = "Circumference (mm)", caption = "Plot by @drsimonj")

## Sign off #

Thanks for reading and I hope this was useful for you.

For updates of recent blog posts, follow @drsimonj on Twitter, or email me at [email protected] to get in touch.

If you’d like the code that produced this blog, check out the blogR GitHub repository.

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