17  ncov2019

remotes::install_github("GuangchuangYu/nCov2019")
remotes::install_github("GuangchuangYu/chinamap")

17.1 全球疫情形势

library(nCov2019)
library(tidyverse)

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.3.6      ✔ purrr   0.3.5 
✔ tibble  3.1.8      ✔ dplyr   1.0.10
✔ tidyr   1.2.1      ✔ stringr 1.4.1 
✔ readr   2.1.3      ✔ forcats 0.5.2 
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

y = load_nCov2019(lang='zh')# 可改为en
d = y['global']

dd <- filter(d, time == time(y) & country != '中国') %>% 
  arrange(desc(cum_confirm)) 

dd = dd[1:40, ]
dd$country = factor(dd$country, levels=dd$country)
dd$angle = 1:40 * 360/40
i = dd$angle > 90 & dd$cum_confirm > dd$cum_confirm[21]
dd$angle[i] = dd$angle[i] + 180
dd$vjust = 1
dd$vjust[i] = 0

as_tibble(dd)

# A tibble: 40 × 7
   time       country cum_confirm cum_heal cum_dead angle vjust
   <date>     <fct>         <int>    <int>    <int> <dbl> <dbl>
 1 2021-03-19 美国       30360639 22523803   552475     9     1
 2 2021-03-19 巴西       11787600 10339432   287795    18     1
 3 2021-03-19 印度       11514331 11083679   159405    27     1
 4 2021-03-19 俄罗斯      4437938  4049373    94267    36     1
 5 2021-03-19 英国        4280882  3593136   125926    45     1
 6 2021-03-19 法国        4181607   278263    91679    54     1
 7 2021-03-19 意大利      3306711  2655346   103855    63     1
 8 2021-03-19 西班牙      3212332  2945446    72910    72     1
 9 2021-03-19 土耳其      2950603  2770638    29777    81     1
10 2021-03-19 德国        2636434  2401413    75071    90     1
# … with 30 more rows

data100_plus<-function(d) d[d$cum_confirm > dd$cum_confirm[21],]
data100_minus<-function(d) d[d$cum_confirm < dd$cum_confirm[21],]

Code

windowsFonts(jianti=windowsFont("dengxian"))
p <- ggplot(dd, aes(country, cum_confirm, fill=cum_confirm)) + 
  geom_col(width=1, color='grey90') + 
  geom_col(aes(y=I(5)), width=1, fill='grey90', alpha = .2) +       
  geom_col(aes(y=I(3)), width=1, fill='grey90', alpha = .2) +    
  geom_col(aes(y=I(2)), width=1, fill = "white") +
  scale_y_log10() + 
  #scale_fill_gradientn(colors=c("darkgreen", "green", "orange", "firebrick","red"), trans="log") + 
  scale_fill_gradientn(colors=c("#57868c","#39bc5c","#c5da27","#eda027","#da400c","#c90d47"),
                       trans="log")+
  geom_text(aes(label=paste(country, cum_confirm, sep="\n"),
                y = cum_confirm *.8, angle=angle, vjust=vjust),
            data= data100_plus(dd),
            size=3, color = "white", fontface="bold",family="jianti")  +
  geom_text(aes(label=paste0(cum_confirm, "例 ", country), 
                y = cum_confirm * 2, angle=angle+90), 
            data= data100_minus(dd), 
            size=3, vjust=0,fontface="bold",family="jianti") +
  coord_polar(direction=-1) + 
  theme_void() + 
  theme(legend.position="none")

ggplotify::as.ggplot(p, scale=1.25, vjust=-.05, hjust=0)

全球疫情形势

17.2