Overview

This Map represent four countries with diverse GDP. One in the south side of the earth, Australia has a higher GDP value compared to northern side countries. Data is from the Worldbank database.

Southern Country: Australia
Northern Countries: Sweden, Finland, and Norway

These countries are geographically located in the northern hemisphere. When comparing certain economic and social indicators, it’s worth noting that the southern country (Australia) generally has a higher GDP per capita, lower income inequality, and other favorable social indicators compared to some of the northern countries (Sweden, Finland, and Norway).

library(tidyverse)
library(WDI)
library(spData)
library(rworldmap)
library(sf)

countries <- c("SWE", "FIN", "NOR", "AUS")
indicators <- c("NY.GDP.PCAP.CD", "SI.POV.GINI", "SE.ADT.LITR.ZS", "SH.XPD.CHEX.PC.CD")

# Retrieve data
data <- WDI(country = countries, 
            indicator = indicators, 
            start = 2019, end = 2019, extra = TRUE)

world_geo<- spData::world%>%
  dplyr::select(iso_a2,geom)

all_data <- world_geo %>%
  left_join(data,by=c("iso_a2"="iso2c"))%>%
  mutate(gpd_country=paste0(NY.GDP.PCAP.CD,",",country))

library(mapview)
#library(lwgeom)
library(rnaturalearth)

world <- rnaturalearth::ne_countries(scale = 'small', 
                                     returnclass = 'sf')

# Fix polygons so they don't get cut in ortho projection
world  <-st_cast(world,'MULTILINESTRING') %>%
  st_cast('LINESTRING', do_split=TRUE) %>%
  mutate(npts = mapview::npts(geometry, by_feature = TRUE)) %>%
  st_cast('POLYGON')

# map
ggplot() +
  geom_sf(data=world, color="gray80",fill=NA) +
  geom_sf(data=all_data,mapping=aes(fill=NY.GDP.PCAP.CD))+
  coord_sf( crs= "+proj=ortho +lat_0=20 +lon_0=-10")

 ggplot() +
  geom_sf(data=world, color="gray80",fill=NA)+
  geom_sf(data=all_data,mapping=aes(fill=NY.GDP.PCAP.CD))+
  coord_sf(crs="ESRI:54030")+
  theme_bw()

sf::st_bbox(world)

sf::st_bbox(all_data)

text=tibble(text=c("The southern country (Australia) generally has a higher GDP per capita, lower income inequality, and other favorable social indicators\ncompared to some of the northern countries (Sweden, Finland, and Norway)."))

ggplot() +
  geom_sf(data=world, color="gray80",fill=NA) +
  geom_sf(data=all_data,
          mapping=aes(fill=factor(round(NY.GDP.PCAP.CD))))+
  scale_fill_manual(
    na.value = "grey90",
    values = (viridis::inferno(4)),
    na.translate = FALSE,
    guide = guide_legend(reverse = TRUE)
  ) +
  # this restricts the map view
  scale_x_continuous(limits = c(-10,20))+
  coord_sf(crs="ESRI:54030",clip = "off")+
  labs(fill="GDP per Capita US($)",
       title="North is not always up",
       subtitle=text$text,
       caption="GDP per capita is gross domestic product divided by midyear population\n\n#30DayMapChallenge 2022 Day 22 North is not always up\nDataSource: WorldBank DataBank - WDI 2019 data| Map: @fgazzelloni")+
  theme_bw(base_size = 14,base_family = "Roboto Condensed")+
  theme(axis.text = element_text(color="red"),
        axis.title = element_blank(),
        plot.title.position = "plot",
        plot.title = element_text(hjust=1,face="bold"),
        plot.subtitle = element_text(size=8,hjust=0.5),
        plot.caption = element_text(size=8,hjust = 0.5),
        legend.key.size = unit(10,units = "pt"),
        legend.text = element_text(size=9),
        legend.title = element_text(size=10))

ggsave("day22_day22_north-is-not-always-up.png",
       width=8)