Only Circular Shapes Map

Only Circular Shapes Map

library(tidyverse)

cases <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv")
deaths <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv")

cases1 <- cases %>%
  pivot_longer(cols = starts_with("X"),
               names_to = "date",
               values_to = "cases") %>%
  mutate(date = gsub("X", "", date),
         date = as.Date(date, format = "%m.%d.%y")) %>%
  janitor::clean_names()

deaths1 <- deaths %>%
  pivot_longer(cols = starts_with("X"),
               names_to = "date",
               values_to = "deaths") %>%
  mutate(date = gsub("X", "", date),
         date = as.Date(date, format = "%m.%d.%y")) %>%
  janitor::clean_names()

COVID19 <- cases1 %>%
  left_join(deaths1, 
            by = c("province_state", 
                   "country_region", 
                   "lat", "long", "date")) %>%
  mutate(cases = ifelse(is.na(cases), 0, cases),
         deaths = ifelse(is.na(deaths), 0, deaths)) %>%
  group_by(country_region, date) %>%
  mutate(cases = sum(cases),
         deaths = sum(deaths),
         cfr = round(deaths / cases, 3)) %>%
  filter(cases > 0) %>%
  arrange(country_region, date)

worldmap <- map_data("world") %>%
  filter(!region == "Antarctica")

centroids <- COVID19 %>%
  group_by(country_region, lat, long) %>%
  reframe(tot_cases = sum(cases),
          tot_deaths = sum(deaths),
          avg_cfr = round(mean(cfr), 3)) %>%
  distinct()

ggplot() +
  geom_polygon(data = worldmap,
               aes(x = long, y = lat, group = group),
               fill = "grey",
               color = "white") +
  geom_point(data = centroids,
             aes(x = long, y = lat,
             size = tot_cases,
             color = log(avg_cfr)), 
             alpha = 0.5) +
  scale_size_continuous(
        labels = scales::unit_format(unit = "M", 
                                     scale = 1e-6)) +
  scale_color_viridis_c() +
  coord_quickmap() +
  labs(title = "COVID-19 Cases by Country",
       caption = "Circle size: total cases, Color: average CFR", 
      size= "Total cases (M)",
      color= "Average CFR (log scale)",
      x = "", y = "") +
  theme(axis.text = element_blank(),
        plot.subtitle = element_text(size = 8))

library(tidyverse)
library(viridis)

# Clean and prepare the data (as in your original script)
cases <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv")
deaths <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv")

cases1 <- cases %>%
  pivot_longer(cols = starts_with("X"),
               names_to = "date",
               values_to = "cases") %>%
  mutate(date = gsub("X", "", date),
         date = as.Date(date, format = "%m.%d.%y")) %>%
  janitor::clean_names()

deaths1 <- deaths %>%
  pivot_longer(cols = starts_with("X"),
               names_to = "date",
               values_to = "deaths") %>%
  mutate(date = gsub("X", "", date),
         date = as.Date(date, format = "%m.%d.%y")) %>%
  janitor::clean_names()

COVID19 <- cases1 %>%
  left_join(deaths1, 
            by = c("province_state", 
                   "country_region", 
                   "lat", "long", "date")) %>%
  mutate(cases = ifelse(is.na(cases), 0, cases),
         deaths = ifelse(is.na(deaths), 0, deaths)) %>%
  group_by(country_region, date) %>%
  mutate(cases = sum(cases),
         deaths = sum(deaths),
         cfr = round(deaths / cases, 3)) %>%
  filter(cases > 0) %>%
  arrange(country_region, date)

centroids <- COVID19 %>%
  group_by(country_region, lat, long) %>%
  reframe(tot_cases = sum(cases),
          tot_deaths = sum(deaths),
          avg_cfr = round(mean(cfr), 3)) %>%
  distinct()

# Create the circular shapes map
ggplot() +
  # Base layer with empty background
  geom_point(data = centroids,
             aes(x = long, y = lat,
                 size = tot_cases,
                 color = log(avg_cfr)), 
             alpha = 0.6) +
  scale_size_continuous(
    range = c(3, 15),  # Adjust size range for better visualization
    labels = scales::unit_format(unit = "M", scale = 1e-6),
    name = "Total Cases (M)"
  ) +
  scale_color_viridis_c(
    option = "magma",  # Use a striking palette
    name = "Avg CFR (log scale)"
  ) +
  coord_quickmap() +
  labs(
    title = "Only Circular Shapes",
    subtitle = "COVID-19 Cases by Country",
    caption = "Size: Total cases | Color: Average CFR (log scale)\n#30DayMapChallenge Day24 | @fgazzelloni",
    x = NULL, y = NULL
  ) +
  ggthemes::theme_map() +
  theme(legend.position = "none",
    panel.background = element_rect(fill = "ghostwhite", color = NA),  # Clean background
    plot.background = element_rect(fill = "white", color = NA),
    plot.title = element_text(size = 22, face = "bold", hjust = 0.5),
    plot.subtitle = element_text(size = 14, hjust = 0.5, color = "gray40"),
    plot.caption = element_text(size = 10, hjust = 0))

Save it as png:

ggsave("day24_only_circular_shapes.png", 
       bg = "white",
       width = 8, height = 6, dpi = 300)