A plot against the CatterPlots complot
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In these terrible times, we R people have more important subjects to debate/care about than ggplot2
vs. base R graphics (isn’t even worth discussing anyway, ggplot2
is clearly the best alternative). Or so I thought until I saw CatterPlots
trending on Twitter this week and even being featured on Revolutions blog. It was cool because plots with cats are cool, but looking more closely at the syntax of CatterPlots
, I couldn’t but realize it was probably a complot to make us all like base R graphics syntax again! So let me show you how to make a cute plot with the awesome ggplot2
extension emojifont
.
The plot I’m going to re-make in this post is an old one already that I designed for celebrating my PhD thesis submission in March last year. I decided to compare the gestation time of my thesis, 1246 days, to the gestation time of some common mammals.
Getting data
I’m a bit ashamed because I forgot to write down where I took my data from but I’m pretty sure it was from reading Wikipedia pages and taking a more or less random numbers in the gestation time range indicated for each animals. I also chose animals I could find an emoji for. As you can imagine, it was quite an agreeable data collection. Here is what I end up with:
library("dplyr")
library("forcats")
gestation <- readr::read_csv2("data/2017-02-18-complot.csv")%>%
arrange(gestation) %>%
mutate(animal = fct_rev(fct_inorder(animal)))
knitr::kable(gestation)
animal | gestation | label | color |
---|---|---|---|
mouse | 19 | mouse | grey |
dog | 61 | dog | grey |
cat | 64 | cat | grey |
wolf | 68 | wolf | grey |
tiger | 105 | tiger | grey |
pig | 112 | pig | grey |
sheep | 144 | sheep | grey |
bear | 220 | bear | grey |
human | 280 | baby | grey |
whale | 590 | whale | grey |
elephant | 617 | elephant | grey |
my thesis | 1246 | closed_book | gold |
levels(gestation$animal)
## [1] "my thesis" "elephant" "whale" "human" "bear"
## [6] "sheep" "pig" "tiger" "wolf" "cat"
## [11] "dog" "mouse"
I used forcats::fct_inorder
and forcats::fct_rev
because in such a post not using forcats
would probably have been a deadly sin (and I don’t have 7 lives), but also because I needed the levels to be ordered from longest to shortest gestation time, otherwise the plot would have looked ugly.
Making the plot
At the time I used gganimate
which I still love, but in the meantime I also fell in love with magick
in particular since reading Bob’s post. So I decided to re-write my code with magick
. On this blog I already published an article featuring both emojifont
and gganimate
.
library("ggplot2")
library("emojifont")
load.emojifont('OpenSansEmoji.ttf')
library("magick")
plot_one_gestation <- function(gestation_time, gestation){
now_data <- filter_(gestation, ~ gestation <= gestation_time)
p <- ggplot(now_data)
p <- p + geom_col(aes(x = animal,
y = gestation,
fill = color))
p <- p +
scale_fill_manual(values = c("grey" = "grey30",
"gold" = "darkgoldenrod1"))
p <- p + geom_text(aes(x = animal,
y = gestation + 45,
label = emoji(label)),
family="OpenSansEmoji", size=30)
p <- p + theme(axis.text.y=element_blank(),
axis.ticks=element_blank(),
text = element_text(size=40),
legend.position="none")
p <- p + ggtitle(gestation_time)
p <- p + scale_x_discrete(limits = levels(gestation$animal))
p <- p + ylim(c(0, max(gestation$gestation) + 50))
p <- p + coord_flip()
p <- p + xlab("Animal")
p <- p + ylab("Gestation in days")
outfil <- paste0("figs/animals_", gestation_time, ".png")
ggsave(outfil, p, width=5, height=5)
outfil
}
I wanted the last image to be repeated 4 times so that everyone might have time to ponder over my accomplishment. I was celebrating and boasting with this graph.
library("purrr")
c(unique(gestation$gestation),
rep(max(gestation$gestation), 3))%>%
map(plot_one_gestation, gestation = gestation) %>%
map(image_read) %>%
image_join() %>%
image_animate(fps=1) %>%
image_write("gestation.gif")
Aren’t these animal emojis adorable? At least as adorable as CatterPlots
cats? You can also bring emojis to ggplot2
with emoGG
(check out Lucy’s recent post) so you don’t need to ever leave the comfort of ggplot2
for the sake of “c[au]t[e]?ness”.
Disclaimer: I actually starred CatterPlots
on Github because I’m an open-minded cat person (married to a cat allergic person!).
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