These kinds of charts are a bit dangerous, as it will be used by anti-EU folk in net contributing countries to say look at how much money we can save when we leave the EU. But this looks only at money being shipped back and forth. The EU has so much benefits in terms of trade and collaboration, it’s a steal at any price.
Exactly. Germany makes way more than 25 billion Euro by being able to freely trade with neighbours.
When you look closely, the most undemocratic of them are also taking the most money…
The only truly undemocratic country on that list is Hungary.
Poland isn’t much better
We’ll see, they just got a new governemnt, I hope the best for them.
Hoping for the best and preparing for the wost is the way of life.
As of now they are undemocratic as hell.
New PM is pro eu and the coalition is democratic. A lot of the judiciary corruption that happened is going to get reversed fast.
Day to day it’s not really undemocratic, it was mostly about popular issues to solidify right wing outrage.
Still, I’m glad it’s over.
We’re there elections in Poland recently? What were the results?
Right “won” but progressives have a majority coalition that just elected a PM. We should be ok.
It’s not all in leftism, but they are in the government, first time since before WW2.
In previous elections “left” was just previous regime surviviors.
Ah good to hear, hopefully they can effect some level of change with the numbers they’ve got
Isn’t a rotten apple enough to spoil the whole basket? At least we have this proverb in my country…
Meanwhile France is doing a police state and Italy elected fascists…
Would be nice to have the same data per capita.
statistia-netcontrib.csv
country,netcontrib DE,25572 FR,12380 NL,6929 IT,3337 SE,2826 DK,1766 AT,1540 FI,1109 IE,703 MT,-14 CY,-172 SI,-386 EE,-729 LT,-860 SK,-1398 LV,-1544 BG,-1727 HR,-1746 ES,-1946 LU,-2020 CZ,-2853 BE,-2950 PT,-3132 RO,-4096 HU,-4206 GR,-4278 PL,-11910
eu-contribution-per-capita.r
if (!require("pacman")) install.packages("pacman") pacman::p_load( countrycode, dplyr, ggdark, ggplot2, r2country ) 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) ggplot(df3, aes(x = percap, y = reorder(name, percap))) + geom_bar(stat = "identity") + dark_theme_gray() + ylab("Country") + xlab("Euros per capita") + scale_x_continuous(breaks = scales::pretty_breaks(n = 20)) + geom_text(aes(label = percap)) ggsave("euros-percap.png")
Sorry about the broken escaping of the angle brackets (“<” is “<”) in the source; Lemmy is, regrettably, broken on that at the moment.
EDIT: Fixed Latvia country code error.
EDIT2: And Austria country code error.
statistia-netcontrib.csvis using some weird country code that isn’t ISO 3166-2, because it’s got what I assume to be Latvia with the codeLAwhich is actually Laos, and that’s reflected on your chart too – I was initially a bit puzzled as to why Laos was listed as being in the EU. At a quick glance it seems to be the only weird one thoughThat’s just me not knowing my country codes. Over here, “LA” is generally Los Angeles. I’ll fix it; thanks.
EDIT: Also, Austria appears to be “AT” rather than “AU”. One more fix.
Ah I thought you pulled that from some Eurostat database and they were using wonky country codes. The AU / AT mixup is a classic one, and since the spelling of Austria and Australia is so close it’s easy to miss that mistake – just like I did
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
Luxembourg and Belgium?
Because the presence of the EU institutions this brings a lot of money in the economy
Would be interesting to see this info per capita.