this post was submitted on 16 Dec 2023
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Europe

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[โ€“] [email protected] 13 points 10 months ago* (last edited 10 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€“] [email protected] 3 points 10 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€“] [email protected] 5 points 10 months ago

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