I’ve written a few times about using an image as an x-axis label, and the solutions have been slowly improving. This one blows all of them out of the water.
Claus Wilke (@ClausWilke) now has a {ggtext} package which can very neatly add images as x-axis labels!
This makes the solution as simple as
library(ggplot2)
library(ggtext)
library(rvest)
## GDP per capita, top 11 countries
url <- "https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita"
html <- xml2::read_html(url)
gdppc <- html_table(html_nodes(html, "table")[3])[[1]][1:11,]
## clean up; remove non-ASCII and perform type conversions
gdppc$Country <- gsub("Â ", "", gdppc$Country)
gdppc$Country <- iconv(gdppc$Country, "latin1", "ASCII", sub="")
gdppc$Country[9] <- "United States of America"
gdppc$Rank <- iconv(gdppc$Rank, "latin1", "ASCII", sub="")
gdppc$`US$` <- as.integer(sub(",", "", gdppc$`US$`))
## switching to a different source of flag images
labels <- setNames(
paste0("<img src='http://www.senojflags.com/images/country-flag-icons/",
gsub(" ", "-", gdppc$Country), "-Flag.png' width='30' /><br>",
sapply(strwrap(gdppc$Country, width = 10, simplify = FALSE),
function(x) paste(x, collapse = "<br>"))),
gdppc$Country
)
## create a dummy dataset
npoints <- length(gdppc$Country)
y <- gdppc$`US$`
x <- gdppc$Country
dat <- data.frame(x=factor(x, levels=gdppc$Country), y=y)
## NB: #85bb65 is the color of money in the USA apparently.
gg <- ggplot(dat, aes(x=x, y=y/1e3L, group=1))
gg <- gg + geom_bar(col="black", fill="#85bb65", stat="identity")
gg <- gg + scale_x_discrete(name = NULL, labels = labels)
gg <- gg + theme_minimal()
gg <- gg + scale_fill_discrete(guide=FALSE)
gg <- gg + theme(plot.background = element_rect(fill="grey90"))
gg <- gg + labs(title="GDP per capita",
subtitle="Top 11 countries",
x="", y="$US/1000",
caption=paste0("Source: ",url))
## ggtext::element_markdown
gg <- gg + theme(axis.text.x = element_markdown(color = "black", size = 7),
axis.text.y = element_text(size=14),
axis.title.x = element_blank())
gg
Figure 1: {ggtext} makes this easy!
This is an even nicer solution than I’ve been using, not only because it’s shorter
to use, but also more flexible - markdown can be processed (using element_markdown)
wherever element_text is used, such as axis text, legends, titles, etc…
I think this finally closes this chapter, but now it’s time to make some really cool graphs with images.
devtools::session_info()
## ─ Session info ──────────────────────────────────────────────────────────
## setting value
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## ui X11
## language en_AU:en
## collate en_AU.UTF-8
## ctype en_AU.UTF-8
## tz Australia/Adelaide
## date 2019-08-13
##
## ─ Packages ──────────────────────────────────────────────────────────────
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## yaml 2.2.0 2018-07-25 [1]
## source
## CRAN (R 3.5.2)
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