R: place geom_text() relative to plot borders rather than fixed position on the plot

Question

I am creating a number of plots using ggplot2 in R and want a way to standardize implementation of a cutoff line. I have data on a number of different measures for four cities over a ~10 year time period. I've plotted them as line graphs with each city a different color within a given graph. I will be creating a plot for each of the different measures I have (around 20).

On each of these graphs, I need to put two cutoff lines (with a word next to them) representing implementation of some policy so that people reading the graphs can easily identify the difference between performance before and after the implementation. Below is approximately the code I'm currently using.

gg_plot1<- ggplot(data=ggdata, aes(x=Year, y=measure1, group=Area, color=Area)) +
  geom_vline(xintercept=2011, color="#EE0000") +
  geom_text(aes(x=2011, label="City1\n", y=0.855), color="#EE0000", angle=90, hjust=0, family="serif") +
  geom_vline(xintercept=2007, color="#000099") +
  geom_text(aes(x=2007, label="City2", y=0.855), color="#000099", angle=0, hjust=1, family="serif") +
  geom_line(size=.75) +
  geom_point(size=1.5) +
  scale_y_continuous(breaks=round(seq(min(ggdata$measure1, na.rm=T), max(ggdata$measure1, na.rm=T), by=0.01), 2)) +
  scale_x_continuous(breaks=min(ggdata$Year):max(ggdata$Year)) +
  scale_color_manual(values=c("#EE0000", "#00DDFF", "#009900", "#000099")) +
  theme(axis.text.x = element_text(angle=90, vjust=1),
        panel.background = element_rect(fill="white", color="white"),
        panel.grid.major = element_line(color="grey95"),
        text = element_text(size=11, family="serif"))

The problem with this implementation is that it relies on placing the two geom_text() on a particular place on the specific graph. These different measures all have different ranges so in order to do this I'd need to go plot by plot and find a spot to place them. What I'd prefer to do is something like force the range of each plot down by X% and put the geom_text() aligned to the bottom of the range. The lines shouldn't need adjusting (same year in every plot), just the position of the text. I found some similar questions here but none that had to do with the specific problem of placing something in the same position on different graphs with different ranges.

Is there a way to do what I'm looking for? If I had to guess, it'd something like using relative positioning rather than absolute but I haven't been able to find away to do that within ggplot. For the record, I'm aware the two geom_text()s are oriented differently. I did that to compare which we prefered but left it for you all. We will ultimately be going with the one that has the text rotated 90deg. Additionally, some of these will be faceted together so that might provide an extra layer of difficulty. Haven't gotten to that point yet.

Sidebar: an alternative way to visualize this would be to change the line from solid to dotted at the cutoff year. Is this possible? I'm not sure the client would want that but I'd love to present it as an option if anyone can point me in the direction of where to learn about how to do that.

Edit to add:

Sample data which shows what happens when running it with different y-ranges

ggdata <- data.frame(Area=rep(c("City1", "City2", "City3", "City4"), times=7),
                     Year=c(rep(2006,4), rep(2007,4), rep(2008,4), rep(2009,4), rep(2010,4), rep(2011,4), rep(2012,4)),
                     measure1=rnorm(28,10,2),
                     measure2=rnorm(28,50,10))

Sample plot which has the geom_text()s in the proper position, but this was done using the code above with a fixed position within the plot. When I replicate the code using a different measure that has a differnet y-range it ends up stretching the plot window.

Answer 1

You can use the y-range of the data to position to the text labels. I've set the y-limits explicitly in the example below, but that's not absolutely necessary unless you want to change them from the defaults. You can also adjust the x-position of the text labels using the x-range of the data. The code below will position the labels at the bottom of the plot, regardless of the y-range of the data.

I've also switched from geom_text to annotate. geom_text overplots the text labels multiple times, once for each row in the data. annotate plots the label once.

ypos = min(ggdata$measure1) + 0.005*diff(range(ggdata$measure1))
xv = 0.02
xh = 0.01
xadj = diff(range(ggdata$Year))

ggplot(data=ggdata, aes(x=Year, y=measure1, group=Area, color=Area)) +
  geom_vline(xintercept=2011, color="#EE0000") +
  geom_vline(xintercept=2007, color="#000099") +
  geom_line(size=.75) +
  geom_point(size=1.5) +
  annotate(geom="text", x=2011 - xv*xadj, label="City1", y=ypos, color="#EE0000", angle=90, hjust=0, family="serif") +
  annotate(geom="text", x=2007 - xh*xadj, label="City2", y=ypos, color="#000099", angle=0, hjust=1, family="serif") +
  scale_y_continuous(limits=range(ggdata$measure1),
                     breaks=round(seq(min(ggdata$measure1, na.rm=T), max(ggdata$measure1, na.rm=T), by=1), 0)) +
  scale_x_continuous(breaks=min(ggdata$Year):max(ggdata$Year)) +
  scale_color_manual(values=c("#EE0000", "#00DDFF", "#009900", "#000099")) +
  theme(axis.text.x = element_text(angle=90, vjust=1),
        panel.background = element_rect(fill="white", color="white"),
        panel.grid.major = element_line(color="grey95"),
        text = element_text(size=11, family="serif"))

UPDATE: To respond to your comment, here's how you can create a separate plot for each "measure" column in your data frame.

First, we create reproducible data with three measure columns:

library(ggplot2)
library(gridExtra)
library(scales)

set.seed(4)
ggdata <- data.frame(Year=rep(2006:2012,each=4),
                     Area=rep(paste0("City",1:4), 7),
                     measure1=rnorm(28,10,2),
                     measure2=rnorm(28,50,10),
                     measure3=rnorm(28,-50,5))

Now, we take the code from above and package it in a function. The function take an argument called measure_var. This is the data column, provided as a character_string, that will provide the y-values for the plot. Note that we now use aes_string instead of aes inside ggplot.

plot_func = function(measure_var) {

  ypos = min(ggdata[ , measure_var]) + 0.005*diff(range(ggdata[ , measure_var]))
  xv = 0.02
  xh = 0.01
  xadj = diff(range(ggdata$Year))

  ggplot(data=ggdata, aes_string(x="Year", y=measure_var, group="Area", color="Area")) +
    geom_vline(xintercept=2011, color="#EE0000") +
    geom_vline(xintercept=2007, color="#000099") +
    geom_line(size=.75) +
    geom_point(size=1.5) +
    annotate(geom="text", x=2011 - xv*xadj, label="City1", y=ypos, 
             color="#EE0000", angle=90, hjust=0, family="serif") +
    annotate(geom="text", x=2007 - xh*xadj, label="City2", y=ypos, 
             color="#000099", angle=0, hjust=1, family="serif") +
    scale_y_continuous(limits=range(ggdata[ , measure_var]),
                       breaks=pretty_breaks(5)) +
    scale_x_continuous(breaks=min(ggdata$Year):max(ggdata$Year)) +
    scale_color_manual(values=c("#EE0000", "#00DDFF", "#009900", "#000099")) +
    theme(axis.text.x = element_text(angle=90, vjust=1),
          panel.background = element_rect(fill="white", color="white"),
          panel.grid.major = element_line(color="grey95"),
          text = element_text(size=11, family="serif")) +
    ggtitle(paste("Plot of", measure_var))
}

We can now run the function once like this: plot_func("measure1"). However, let's run it on all the measure columns in one go by using lapply. We give lapply a vector with the names of the measure columns (names(ggdata)[grepl("measure", names(ggdata))]), and it runs plot_func on each of these columns in turn, storing the resulting plots in the list plot_list.

plot_list = lapply(names(ggdata)[grepl("measure", names(ggdata))], plot_func)

Now if we wish, we can lay them all out together using grid.arrange. In this case, we only need one legend, rather than a separate legend for each plot, so we extract the legend as a separate graphical object and lay it out beside the three plots.

# Function to get legend from a ggplot as a separate graphical object
# Source: https://github.com/tidyverse/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs/047381b48b0f0ef51a174286a595817f01a0dfad
g_legend<-function(a.gplot){
  tmp <- ggplot_gtable(ggplot_build(a.gplot))
  leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
  legend <- tmp$grobs[[leg]]
  return(legend)
}

# Get legend
leg = g_legend(plot_list[[1]])

# Lay out all of the plots together with a single legend
grid.arrange(arrangeGrob(grobs=lapply(plot_list, function(x) x + guides(colour=FALSE))),
             leg,
             ncol=2, widths=c(10,1))