Automate tick max and min in faceted ggplot - r

Question

I am trying to just mark the max and min of each x-axis in a faceted ggplot. I have several facets with different x scales and the same y scale, and the x axis tick labels overlap each other. Rather than having to manually determine the limits and breaks for each facet x axis, I am looking for a way to just label the min and max values for each.
Code using example data of the CO2 dataset (see ?CO2):
CO2$num <- 1:nrow(CO2)
library(reshape2)
CO2.melt <- melt(CO2,
id.var=c("Type",
"Plant",
"Treatment",
"num"))
CO2.melt <- CO2.melt[order(CO2.melt$num),]
library(ggplot2)
ggplot(CO2.melt,
aes(x = value,
y = num)) +
geom_path(aes(color = Treatment)) +
facet_wrap( ~ variable, scales = "free_x",nrow=1)
Purpose is to replicate well log displays such as this one.

Answer 1

When you want to implemented this for the tick-labels, the use of scales = "free_x" in a faceted plot makes this hard to automate this. However, with a bit of tinkering and the help of several other packages, you could also use the following approach:
1) Summarise the data in order to get an idea which tick-labels / breaks you need on the x-axis:
library(data.table)
minmax <- melt(setDT(CO2.melt)[, .(min.val = min(value), max.val = max(value),
floor.end = 10*ceiling(min(value)/10),
ceil.end = 10*floor((max(value)-1)/10)),
variable][],
measure.vars = patterns('.val','.end'),
variable.name = 'var',
value.name = c('minmax','ends'))
which gives:
> minmax
variable var minmax ends
1: conc 1 95.0 100
2: uptake 1 7.7 10
3: conc 2 1000.0 990
4: uptake 2 45.5 40
2) Create break vecors for each facet:
brks1 <- c(95,250,500,750,1000)
brks2 <- c(7.7,10,20,30,40,45.5)
3) Create the facets:
p1 <- ggplot(CO2.melt[CO2.melt$variable=="conc",],
aes(x = value, y = num, colour = Treatment)) +
geom_path() +
scale_x_continuous(breaks = brks1) +
theme_minimal(base_size = 14) +
theme(axis.text.x = element_text(colour = c('red','black')[c(1,2,2,2,1)],
face = c('bold','plain')[c(1,2,2,2,1)]),
axis.title = element_blank(),
panel.grid.major = element_line(colour = "grey60"),
panel.grid.minor = element_blank())
p2 <- ggplot(CO2.melt[CO2.melt$variable=="uptake",],
aes(x = value, y = num, colour = Treatment)) +
geom_path() +
scale_x_continuous(breaks = brks2) +
theme_minimal(base_size = 14) +
theme(axis.text.x = element_text(colour = c('red','black')[c(1,2,2,2,2,1)],
face = c('bold','plain')[c(1,2,2,2,2,1)]),
axis.title = element_blank(),
panel.grid.major = element_line(colour = "grey60"),
panel.grid.minor = element_blank())
4) Extract the legend into a separate object:
library(grid)
library(gtable)
fill.legend <- gtable_filter(ggplot_gtable(ggplot_build(p2)), "guide-box")
legGrob <- grobTree(fill.legend)
5) Create the final plot:
library(gridExtra)
grid.arrange(p1 + theme(legend.position="none"),
p2 + theme(legend.position="none"),
legGrob, ncol=3, widths = c(4,4,1))
which results in:
A possible alternative solution to do this automatically, is either use geom_text or geom_label. An example to show how you can achieve this:
# create a summary
library(dplyr)
library(tidyr)
minmax <- CO2.melt %>%
group_by(variable) %>%
summarise(minx = min(value), maxx = max(value)) %>%
gather(lbl, val, -1)
# create the plot
ggplot(CO2.melt, aes(x = value, y = num, color = Treatment)) +
geom_path() +
geom_text(data = minmax,
aes(x = val, y = -3, label = val),
colour = "red", fontface = "bold", size = 5) +
facet_wrap( ~ variable, scales = "free_x", nrow=1) +
theme_minimal()
which gives:
You can also get the minimum and maximum values on the fly inside ggplot (credit to #eipi10). Another example using geom_label:
ggplot(CO2.melt, aes(x = value, y = num, color = Treatment)) +
geom_path() +
geom_label(data = CO2.melt %>%
group_by(variable) %>%
summarise(minx = min(value), maxx = max(value)) %>%
gather(lbl, val, -1),
aes(x = val, y = -3, label = val),
colour = "red", fontface = "bold", size = 5) +
facet_wrap( ~ variable, scales = "free_x", nrow=1) +
theme_minimal()
which gives:

Answer 2

Edit Updating to ggplot2 ver 3.0.0
This approach modifies the labels in the ggplot build data (i.e., ggplot_build(plot)). I've removed the x-axis expansions so that the maximum and minimum values fall on the panel boundaries.
# Packages
library(grid)
library(ggplot2)
library(reshape2)
# Data
CO2$num <- 1:nrow(CO2)
library(reshape2)
CO2.melt <- melt(CO2,
id.var=c("Type",
"Plant",
"Treatment",
"num"))
CO2.melt <- CO2.melt[order(CO2.melt$num),]
# Plot
(p <- ggplot(CO2.melt,
aes(x = value,
y = num)) +
scale_x_continuous(expand = c(0, 0)) +
geom_path(aes(color = Treatment)) +
facet_wrap( ~ variable, scales = "free_x", nrow=1))
# Get the build data
gb <- ggplot_build(p)
# Get number of panels
panels = length(gb$layout$panel_params)
# Get x tick mark labels
x.labels = lapply(1:panels, function(N) gb$layout$panel_params[[N]]$x.labels)
# Get range of x values
x.range = lapply(1:panels, function(N) gb$layout$panel_params[[N]]$x.range)
# Get position of x tick mark labels
x.pos = lapply(1:panels, function(N) gb$layout$panel_params[[N]]$x.major)
# Get new x tick mark labels - includes max and min
new.labels = lapply(1:panels, function(N) as.character(sort(unique(c(as.numeric(x.labels[[N]]), x.range[[N]])))))
# Tag min and max values with "min" and "max"
new.labelsC = new.labels
minmax = c("min", "max")
new.labelsC = lapply(1:panels, function(N) {
x = c(new.labelsC[[N]][1], new.labelsC[[N]][length(new.labels[[N]])])
x = paste0(x, "\n", minmax)
c(x[1], new.labelsC[[N]][2:(length(new.labels[[N]])-1)], x[2])
} )
# # Get position of new labels
new.pos = lapply(1:panels, function(N) (as.numeric(new.labels[[N]]) - x.range[[N]][1])/(x.range[[N]][2] - x.range[[N]][1]))
# Put them back into the build data
for(i in 1:panels) {
gb$layout$panel_params[[i]]$x.labels = new.labelsC[[i]]
gb$layout$panel_params[[i]]$x.major_source = as.numeric(new.labels[[i]])
gb$layout$panel_params[[i]]$x.major = new.pos[[i]]
}
# Get the ggplot grob
gp = ggplot_gtable(gb)
# Add some additional space between the panels
pos = gp$layout$l[grep("panel", gp$layout$name)] # Positions of the panels
for(i in 1:(panels-1)) gp$widths[[pos[i]+1]] = unit(1, "cm")
# Colour the min and max labels using `grid` editing functions
for(i in 1:panels) {
gp = editGrob(grid.force(gp), gPath(paste0("axis-b-", i), "axis", "axis", "GRID.text"),
grep = TRUE, gp = gpar(col = c("red", rep("black", length(new.labels[[i]])-2), "red")))
}
# Draw it
grid.newpage()
grid.draw(gp)