Highlighting individual axis labels in bold using

Question

I want to highlight individual axis labels in bold. I am aware of this answer by @MrFlick but I can't figure out how to do this a) for more than one item, and b) whether it's possible to use the names of the labels instead of the number of the item in that list (or expression).

Here is an example dataset:

require(ggplot2)
require(dplyr)
set.seed(36)
xx<-data.frame(YEAR=rep(c("X","Y"), each=20),
               CLONE=rep(c("A","B","C","D","E"), each=4, 2),
               TREAT=rep(c("T1","T2","T3","C"), 10),
               VALUE=sample(c(1:10), 40, replace=T))

Then I am sorting my labels according to a particular factor combination which is then supposed to be maintained across multiple panels of a plot. See my previous question here.

clone_order <- xx %>% subset(TREAT == "C"  & YEAR == "X") %>%
  arrange(-VALUE) %>% select(CLONE) %>% unlist()    
xx <- xx %>% mutate(CLONE = factor(CLONE, levels = clone_order))

ggplot(xx, aes(x=CLONE, y=VALUE, fill=YEAR)) + 
  geom_bar(stat="identity", position="dodge") +
  facet_wrap(~TREAT)

Now I want to bold Clone A, B and E. I am sure this will work somehow but I cannot figure out how. Ideally, it would be great to know how to do this by a) using the number of the item in the list/expression, and b) by using the label, e.g. A, B and E.

Answer 1

Here's a generic method to create the emboldening vector:

colorado <- function(src, boulder) {
  if (!is.factor(src)) src <- factor(src)                   # make sure it's a factor
  src_levels <- levels(src)                                 # retrieve the levels in their order
  brave <- boulder %in% src_levels                          # make sure everything we want to make bold is actually in the factor levels
  if (all(brave)) {                                         # if so
    b_pos <- purrr::map_int(boulder, ~which(.==src_levels)) # then find out where they are
    b_vec <- rep("plain", length(src_levels))               # make'm all plain first
    b_vec[b_pos] <- "bold"                                  # make our targets bold
    b_vec                                                   # return the new vector
  } else {
    stop("All elements of 'boulder' must be in src")
  }
}

ggplot(xx, aes(x=CLONE, y=VALUE, fill=YEAR)) + 
  geom_bar(stat="identity", position="dodge") +
  facet_wrap(~TREAT) +
  theme(axis.text.x=element_text(face=colorado(xx$CLONE, c("A", "B", "E"))))

Answer 2

You can create a named vector of expressions (that turn text to bold) in scale_x_discrete and use parse=TRUE to evaluate the expressions:

ggplot(xx, aes(x=CLONE, y=VALUE, fill=YEAR)) + 
    geom_bar(stat="identity", position="dodge") +
    facet_wrap(~TREAT) +
    scale_x_discrete(labels=c("A"=expression(bold(A)), "C"=expression(bold(C)),
                              "E"=expression(bold(E)), parse=TRUE))

You can probably create the vector of expressions programmatically, rather than typing it out, but the way to do that is escaping me right now.

Answer 3

I'm not sure if you can map label characteristics by name, but it's definitely possible to do it by position with a call to theme:

ggplot(xx, aes(x=CLONE, y=VALUE, fill=YEAR)) + 
  geom_bar(stat="identity", position="dodge") +
  facet_wrap(~TREAT) +
  theme(axis.text.x = element_text(face = c('bold', 'bold', 'plain', 'plain', 'bold')))

Note that the listed font faces for axis.text.x are the same length as the labels of your x-axis (five elements). This produces: