Thanks Hanna! Hope all is well and the PhD is off to a good start!

Thanks! The plots are mostly due to some earlier procrastination making a little package with custom ggplot themes and palettes + some functions to set geom defaults etc. github.com/drcaprosser/...

Thanks - pleased with those! Font awesome makes getting the icons nice and easy - add this to your header-includes:
- \usepackage{fontawesome5}
And then call the icons as latex, e.g.
author:
- |
Name^[\faUniversity\ Uni name]

Getting them to line up nicely, however, was a massive pain...

Nice, thanks for the code!

That is a cool plot! Presumably gganimate in some form?

Hehe, I'm choosing to believe that someone in the government read this paper and this is why they're doing the policy.

Perhaps you would like to join my new grant bid: 'The impact of restaurants on political attitudes: an autoethnographic approach'

😱 And here I was just doing regular snarking about causal salads...

I mean there was this one time this South African guy I lived as a student made dinner, and before that... 😉

I'm concerned that this time series *starts* after midnight 😂

Well sure, but it's the same thing as Starmer saying 'two-thirds of our children should go either to university or take a gold-standard apprenticeship' today.

Not sure that's really true - at the 1999 conference Blair said 'today I set a target of 50 per cent of young adults going into higher education in the next century' news.bbc.co.uk/1/hi/uk_poli...

It's the first R package I've made, and I won't lie - I had help from ChatGPT. I'm pretty good at R for statistics, but I'm not a programmer...

Anyway I'm quite pleased with it, so do have a look if you think this might be useful!

With one line of code you can assign party colours and labels, and sort the legend.

library(gbpartyscales)

share_plot +
scale_colour_party()

Imagine you had a dataset of British elections results and wanted to make a plot.

share_plot <- gb_shares %>%
ggplot(aes(x = Election, y = `GB vote %`, colour = Party)) +
geom_line() +
geom_point(size = 3) +
theme_bw() +
scale_x_continuous(breaks = c(2019, 2024))

share_plot

The package provides a bunch of scale_*_party() functions that slot into ggplot in the same way that ggplot's scale_* functions work and colour and label the parties by matching party names to aliases.

There's also a party_factor() function that turns party into a labelled and sorted factor.