{ggtext} for images as x-axis labels

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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("
", sapply(strwrap(gdppc$Country, width = 10, simplify = FALSE), function(x) paste(x, collapse = "
"))), gdppc$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

{ggtext} makes this easy!

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                       
##  version  R version 3.5.2 (2018-12-20)
##  os       Pop!_OS 19.04               
##  system   x86_64, linux-gnu           
##  ui       X11                         
##  language en_AU:en                    
##  collate  en_AU.UTF-8                 
##  ctype    en_AU.UTF-8                 
##  tz       Australia/Adelaide          
##  date     2019-08-13                  
## 
## ─ Packages ──────────────────────────────────────────────────────────────
##  package     * version   date       lib
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##  ggplot2     * 3.2.1     2019-08-10 [1]
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##  source                              
##  CRAN (R 3.5.2)                      
##  CRAN (R 3.5.2)                      
##  CRAN (R 3.5.2)                      
##  Github (rstudio/[email protected])   
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