ggplot2 案例：使用 ggplot2 绘制绘制一幅气泡地图展示各国疫情状况

library(ggplot2)
library(sf)
library(readr)
library(dplyr)

worldmap <- read_sf('world.geo.json') %>%
  st_transform(crs = 4326)

read_csv('time_series_19-covid-Confirmed.csv') %>%
  select(Lat, Long, `3/4/20`) %>%
  `colnames<-`(c("lat", "long", "con")) %>%
  st_as_sf(coords = c("long", "lat"), crs = 4326) -> con_df

mybreaks <- c(1, 20, 100, 1000, 50000)
ggplot(worldmap) +
  geom_sf(size = 0.1, color = "white", fill = NA) +
  geom_sf(data = con_df, aes(size = con,
                             color = con)) +
  theme_modern_rc(base_family = cnfont,
                  subtitle_family = cnfont,
                  caption_family = cnfont,
                  grid = "") +
  worldtilegrid::theme_enhance_wtg() +
  theme(panel.grid = element_blank()) +
  scale_size_continuous(name = "Confirmed cases",
                        trans = "log",
                        range = c(1, 7),
                        breaks = mybreaks,
                        labels = c("1-19", "20-99", "100-999", "1,000-49,999", "50,000+")) +
  scale_color_viridis_c(option = "inferno",
                        name = "Confirmed cases",
                        trans = "log",
                        breaks = mybreaks,
                        labels = c("1-19", "20-99", "100-999", "1,000-49,999", "50,000+")) +
  guides(color = guide_legend()) +
  labs(title = "新冠肺炎的全球分布",
       subtitle = "截止：2020 年 3 月 4 日",
       caption = "数据来源: CSSEGISandData/COVID-19: Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE\nhttps://github.com/CSSEGISandData/COVID-19\n绘制：TidyFriday")