PLOTS/COVID19 CASES US SPA ITA US SK at master · mlamias/PLOTS · GitHub

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require(RCurl)
require(foreign)
require(tidyverse) # To tip the df from long row of dates to cols (pivot_longer())
x = getURL("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv")

corona <- read.csv(textConnection(x))
corona = (read_csv(x)
          %>% pivot_longer(cols = -c(`Province/State`, `Country/Region`, Lat, Long),
                           names_to = "date",
                           values_to = "cases")
          %>% select(`Province/State`, `Country/Region`, date, cases)
          %>% mutate(date=as.Date(date,format="%m/%d/%y"))
          %>% drop_na(cases)
          %>% rename(provinces=`Province/State`, country=`Country/Region`)
)

cc <- (corona
       %>% filter(country %in% c("Italy","Spain", "Korea, South","US"))
)

ccw <- (cc
        %>% pivot_wider(names_from="country",values_from="cases")
        %>% filter(cumsum(Italy>0 & Spain>0)>=2)
)


china <- corona[corona$country=='China',]
provinces <- c('Hubei', 'Guangdong', 'Henan', 'Zhejiang', 'Hunan', 'Anhui',
               'Jiangxi','Shandong','Jiangsu','Sichuan','Heilongjiang','Hebei',
               'Fujian','Guangxi','Shaanxi','Yunnan','Hainan','Guizhou','Shanxi',
               'Gansu','Hong Kong','Liaoning','Jilin','Xinjiang','Inner Mongolia',
               'Ningxia','Qinghai','Macau','Tibet')

china_prov <- china[is.element(china$provinces,provinces),]
ccchina <- china_prov[,2:4]
temp <- aggregate(ccchina[ ,3], FUN="sum", by=list(as.Date(ccchina$date)))
ccchina[1:nrow(temp),2:3] <- temp
ccchina <- ccchina[1:nrow(temp),]

ccw_china <- (ccchina
              %>% pivot_wider(names_from=country,values_from="cases")
              %>% filter(China>1)
)


plot(ccw$date, ccw$US, type="l", lwd=3, lty=1,
     ylab='',
     xlab='',
     log='y',
     col=1,
     axes=FALSE,
     main = "Log-lin cumulative COVID-19 cases in Italy, Spain, US v SK & China",
     cex.main=0.9,
     cex.main=0.9)

at1 <- seq(min(ccw$date), max(ccw$date)+1, by=2);
axis.Date(1, at=at1, format="%b %d", las=2, cex.axis=0.7)


at2 <- 2^seq(1,30,by=1)
axis(side=2, at2, cex.axis=0.7, las=2)

abline(h=at2, lty=2, col="grey90")  # Add faint grid lines
abline(v=at1, lty=2, col="grey90")  # Add faint grid lines


lines(ccw$date, ccw$US, type="l", lwd=3, col=1)
lines(ccw$date, ccw$Italy, type="l", lwd=3, col=4)
lines(ccw$date, ccw$`Korea, South`, lwd=3, col=5, lty=3)
lines(ccw$date, ccw$Spain, lwd=3, col=2)
lines(ccw_china$date, ccw_china$China, lwd=3, lty= 3, col=7)


legend(ccw$date[1], 5000,
       legend=c("China", "Korea", "Italy", "Spain", "US"),
       col=c(7,5,4,2,1), lty=c(3,3,1,1,1), lwd=3, cex=0.8,
       box.lty=0)


plot(ccw$date, ccw$US, type="l", lwd=3, lty=1,
     ylab='',
     xlab='',
     col=1,
     axes=F,
     cex.axis=0.7,
     las=2,
     main = "Cumulative COVID-19 cases in Italy, Spain, US v SK & China",
     cex.main=0.9,
     bty='l')

at1 <- seq(min(ccw$date), max(ccw$date)+1, by=2);
axis.Date(1, at=at1, format="%b %d", las=2, cex.axis=0.7)

at2 <- seq(0, 1000000, by=20000);
axis(side=2, at2, cex.axis=0.7, las=2)

abline(v=at1, lty=2, col="grey90")  # Add faint grid lines
abline(h=at2, lty=2, col="grey90")  # Add faint grid lines

lines(ccw$date, ccw$US, lwd=3, col=1)
lines(ccw$date, ccw$Italy, lwd=3, col=4)
lines(ccw$date, ccw$Spain, lwd=3, col=2)
lines(ccw$date, ccw$`Korea, South`, lwd=3, lty=3, col=5)
lines(ccw_china$date, ccw_china$China, lwd=3, lty=3, col=7)

legend(ccw$date[1], 200000,
       legend=c("China","Korea", "Italy", "Spain", "US"),
       col=c(7,5,4, 2, 1), lty=c(3,3,1,1,1), lwd=3, cex=0.8,
       box.lty=0)