Hexagons

Overview

Hexagons map of Covid19 data in Italy. For this challenge I will be using the {covid19italy} package for mapping Covid19 cases in Italy.

Italy

library("sf")
library("tidyverse")
library("rnaturalearth")
library("covid19italy")

italy_geo <- ne_states(#scale = "large",
                   country = "Italy",
                   returnclass = "sf") |>
  st_geometry() |> ## 
  st_transform(3003) 

italy_map <- ne_states(#scale = "large",
                   country = "Italy",
                   returnclass = "sf")

italy_map%>%names

italy_map_region <- italy_map%>%count(region)

italy_geo |> 
  ggplot() +
  geom_sf(fill = "white", color = "pink") +
  geom_sf(data=italy_map,
          mapping=aes(fill=region),
          color="pink",
          inherit.aes = F)+
  labs(fill="")+
  ggthemes::theme_map()+
  theme(legend.position = "bottom",
        legend.key.size = unit(5,units="pt"),
        legend.text = element_text(size=5))

Italy Hexagons

hexgrid <- st_make_grid(italy_geo,
                        cellsize = 1e4, 
                        what = 'polygons',
                        square = FALSE ## !
                        ) %>%
  st_as_sf()

hexgrid_italy <- hexgrid[c(unlist(st_contains(italy_geo, hexgrid)), 
                        unlist(st_overlaps(italy_geo, hexgrid))) ,] 

italy_geo |> 
  ggplot() +
  geom_sf(fill = "#8c8b8b", color = "#7cb3b8") +
geom_sf(data = hexgrid_italy, 
        color = "#43605b") +
  labs(title = "Italy", 
       caption = "#30DayMapChallenge | Day 9: Hexagons | Map: @fgazzelloni")+
  ggthemes::theme_map()

Hexagons by region

italy_geo |> 
  ggplot() +
  geom_sf(color = "pink") +
  geom_sf(data=italy_map,
          mapping=aes(fill=region),
          alpha=0.5,
          color=NA,
          inherit.aes = F)+
  geom_sf(data = hexgrid_italy_reg, 
          fill=NA,
        color = "#43605b") +
    labs(title = "Italy", 
       caption = "#30DayMapChallenge | Day 9: Hexagons | Map: @fgazzelloni")+
  labs(fill="")+
  ggthemes::theme_map()+
  theme(legend.position = "bottom",
        legend.key.size = unit(5,units="pt"),
        legend.text = element_text(size=5))

italy_map_region_covid <- italy_map_region %>%
  left_join(covid19italy::italy_region %>% 
              filter(date == max(date)), 
            by = c("region" = "region_spatial"))

italy_map_region_covid%>%names

italy_geo |> 
  ggplot() +
  geom_sf(color = "#8c8b8b") +
  geom_sf(data=italy_map_region_covid,
          mapping=aes(fill=death),
          color=NA,
          inherit.aes = F)+
  geom_sf(data = hexgrid_italy_reg, 
          fill=NA,
        color = "#FFDAB9") +
  scale_fill_gradientn(colors=rev(c("#FF4500","#FFA500","#FFD700")))+
    ggtext::geom_richtext(x=2401390 ,y=4837570,
                        hjust = 1,
                        vjust=0,
                        label="Italy",
                        fill = NA, 
                        color="#8c8b8b",
                        label.color = NA,
                        size=25,
                        family = "Roboto Condensed")+
      ggtext::geom_richtext(x=2401390 ,y=4737570,
                        hjust = 0.8,
                        vjust=0,
                        color="#8c8b8b",
                        label="Total number of Covid19 death cases",
                        fill = NA, 
                        label.color = NA,
                        size=4,
                        family = "Roboto Condensed")+
    labs(caption = "#30DayMapChallenge 2023 Day 9 Hexagons\nDataSource: {covid19italy} data| Map: @fgazzelloni",
       fill="N. Deaths")+
  ggthemes::theme_map()+
  coord_sf(clip = "off")+
  theme(text=element_text(color="#8c8b8b",family="Roboto Condensed"),
        plot.caption = element_text(hjust = 0.5,size=8,face = "bold"),
        legend.position = "bottom",
        legend.background = element_rect(color="#8c8b8b",fill="#FFDAB9"),
        legend.key.size = unit(10,units="pt"),
        legend.text = element_text(size=5))+
   ggspatial::annotation_scale()

ggsave("day9_hexagons.png", 
       dpi = 320, bg="#FFDAB9")

Source of inspiration: https://github.com/umemasiddiqi/30DayMapChallenge/blob/main/2023/11092023/Pak-Hexagon.R

Covid-19 Italy

Source of data: https://covid19r.github.io/covid19italy/articles/geospatial_visualization.html