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.
this post was submitted on 16 Dec 2023
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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
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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 (โ<โ is โ<โ) 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.csv is using some weird country code that isn't ISO 3166-2, because it's got what I assume to be Latvia with the code LA which is actually Laos, and that's reflected on your chart too โ 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 though
That'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 โ 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.