•  tal   ( @tal@lemmy.today ) English
      20•7 months ago

      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")

      Full size image

      Sorry about the broken escaping of the angle brackets (“<” is “&lt;”) in the source; Lemmy is, regrettably, broken on that at the moment.

      EDIT: Fixed Latvia country code error.

      EDIT2: And Austria country code error.

      •  interolivary   ( @interolivary@beehaw.org ) English
        11•7 months ago

        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 – 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

        •  tal   ( @tal@lemmy.today ) English
          7•7 months ago

          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.

          •  interolivary   ( @interolivary@beehaw.org ) English
            2•7 months ago

            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

      •  tal   ( @tal@lemmy.today ) English
        5•7 months ago

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

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

df3 &lt;- 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