Data day

To cite Federica’s work please use:

Gazzelloni F. (2023), Data Visualization: Eurosat hlth_hlye data

library(tidyverse)
# install.packages("eurostat")
library(eurostat)
library(sf)
library(countrycode)

id <- search_eurostat("Healthy life years by sex")
id <- id[1,]
id
# save(id,file="id.RData")

data <- get_eurostat("hlth_hlye",unit="PC")
# save(data,file="data.RData")

df <- data%>%
  filter(indic_he=="HLY_PC_0")%>%
  mutate(year=year(time))%>%
  select(geo, year,sex,values)%>%
  mutate(sex=case_when(sex=="F"~"Female",
                       sex=="M"~"Male",
                       TRUE~"Both"))
df%>%head

my_countries_abbr <- unique(df$geo)

# countrycode::codelist%>%names

my_countries <- countrycode::codelist %>%
  count(country.name.en, iso2c) %>%
  filter(iso2c %in% my_countries_abbr)%>%
  rename(region=country.name.en)

my_countries_names <- unique(my_countries$region)

df_countries <- df%>%
  inner_join(my_countries,by=c("geo"="iso2c"))

df_countries%>%head

df_geometry <- map_data("world") %>%
  filter(region %in% my_countries_names) %>%
  group_by(group) %>%
  sf::st_as_sf(coords = c(1, 2), crs = 4326) %>%
  summarise(geometry = st_combine(geometry)) %>%
  st_cast("POLYGON") 

df_geometry %>% head

polygons <- rnaturalearth::ne_countries(returnclass = "sf")

ggplot()+
  geom_sf(data=polygons)+
  geom_sf(data=df_geometry,aes(geometry=geometry),color="red")

df_coords <- map_data("world") %>%
  filter(region %in% my_countries_names)%>%
  select(region,group)

df_full <- df_geometry%>%
  inner_join(df_coords,by="group") %>% 
  merge(df_countries,by="region")


austria <- df_full%>%
  filter(region=="Austria",year==2020)

polygons <- rnaturalearth::ne_countries(scale = 110, 
                                        type = 'map_units',
                                        returnclass = 'sf')

ggplot()+
  geom_sf(data=polygons)+
  geom_sf(data=df_geometry,aes(geometry=geometry),fill="beige")+
  geom_sf(data=austria,aes(geometry=geometry,fill=values))+
  coord_sf()

Zooming in

source: https://www.r-bloggers.com/2019/04/zooming-in-on-maps-with-sf-and-ggplot2/

# polygons%>%View

my_countries_names[30]<- "England"
my_countries_names[31]<- "N. Ireland"
my_countries_names[32]<- "Scotland"
my_countries_names[33]<- "Wales"
eu <- polygons[polygons$name %in% my_countries_names,]
ggplot() + geom_sf(data = eu) + theme_bw()

eu_qualy <- df_full%>%
  filter(year==2020)

map <- ggplot()+
  geom_sf(data=eu)+
  geom_sf(data=df_geometry,aes(geometry=geometry),fill="beige")+
  geom_sf(data=eu_qualy,aes(geometry=geometry,fill=values))+
  coord_sf()+
  facet_wrap(~sex)

map

map +
  scale_fill_gradient(low = "white",high = "#a60845") +
  labs(title="Healthy life years by sex (2020) %",
       caption="DataSource: Eurosat - Healthy life years by sex\n#30DayChartChallenge day18 Eurosat | DataViz: Federica Gazzelloni") +
  ggthemes::theme_map(base_size = 12, base_family = "Roboto Condensed")+
  theme(strip.background = element_rect(color = "#a60845",fill="#a60845"),
        strip.text = element_text(color="white"),
        legend.position = "bottom",
        plot.title = element_text(color="#a60845",size=20),
        plot.caption = element_text(color="#a60845",size=12))

ggsave("map.png",width = 7,height = 5)