this post was submitted on 16 Dec 2023
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Europe

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[โ€“] tal@lemmy.today 13 points 7 months ago* (last edited 7 months ago) (1 children)

Also, a Markdown table rendition:

eu-contribution-per-capita-markdown.r

if (!require("pacman")) install.packages("pacman")
pacman::p_load(
            countrycode,
            dplyr,
            r2country,
            simplermarkdown
        )

abs <- read.csv("statista-netcontrib.csv",header = TRUE)
abs2 <- cbind(abs,name = countrycode(abs$country,"iso2c","country.name")) 

df <- inner_join(country_names, abs2)
df2 <- inner_join(country_population, df)
df2$percap <- df2$netcontrib/df2$population2023*1000000

df3 <- arrange(df2,-percap)

md_table(df3)

name percap
Netherlands 386.91124
Germany 302.86855
Denmark 297.09908
Sweden 267.98643
Finland 199.90810
France 181.71677
Austria 168.68113
Ireland 136.52768
Italy 56.76638
Malta -26.94577
Spain -40.25217
Slovenia -182.27546
Cyprus -187.34343
Romania -214.99549
Belgium -250.73894
Slovakia -257.60767
Bulgaria -267.84703
Portugal -299.21568
Lithuania -300.05251
Poland -315.86485
Greece -408.10926
Hungary -438.25808
Croatia -449.01298
Estonia -533.72029
Latvia -819.79399
Luxembourg -3056.85909
[โ€“] Whelks_chance@lemmy.world 3 points 7 months ago (1 children)

This is very clever. Is Lemmy actually running the code to achieve this, or did you paste it just so other people can replicate the process?

[โ€“] tal@lemmy.today 5 points 7 months ago

Nah, I just pasted it so that other people can reproduce.