PLOTS/COVID19_US_China 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_19-covid-Confirmed.csv")

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)
)

united <- corona[corona$`Country/Region`=='US',]
cc_no_states <- united[!united$`Province/State`%in%state.name,]
ccn <- cc_no_states[,2:4]

cc_with_states <- corona[is.element(corona$`Province/State`,state.name),]
cc <- cc_with_states[,2:4]

mix <- rbind(ccn,cc)
mix <- aggregate(mix[,3], FUN="sum", by=list(as.Date(mix$date)))


cc[,2:3] <- mix
cc <- cc[1:nrow(mix),]

china <- corona[corona$`Country/Region`=='China',]
provinces <- c('Hubei', 'Guangdong', 'Henan', 'Zhejiang', 'Hunan', 'Anhui',
               'Jiangxi','Shandong','Jiangsu','Sichuan','Heilongjiang','Hebei',
               'Fujian','Guangxi','Shaanxi','Yunnan','Hainan','Guizhou','Shanxi',
               'Gansu','Hong Kong','Liaoning','Jilin','Xinjiang','Inner Mongolia',
               'Ningxia','Qinghai','Macau','Tibet')
china_prov <- china[is.element(china$`Province/State`,provinces),]
ccchina <- china_prov[,2:4]
temp <- aggregate(ccchina[ ,3], FUN="sum", by=list(as.Date(ccchina$date)))
ccchina[,2:3] <- temp
ccchina <- ccchina[1:nrow(temp),]

ccw <- (cc
        %>% pivot_wider(names_from=`Country/Region`,values_from="cases")
        %>% filter(US>1)
)

ccw_china <- (ccchina
        %>% pivot_wider(names_from=`Country/Region`,values_from="cases")
        %>% filter(China>1)
)


plot(ccw_china$date, ccw_china$China, type="l", lwd=3, lty=3,
     ylab='',
     xlab='',
     log='y',
     col=5,
     axes=FALSE,
     main = "Log-lin cumulative COVID-19 cases in US v China",
     cex.main=0.9)

at1 <- seq(min(ccw_china$date), max(ccw_china$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)

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, lwd=3, col=4)

legend(ccw_china$date[1], 70000, legend=c("China", "US"),
       col=c(5, 4), lty=c(3,1), lwd=3, cex=0.8,
       box.lty=0)


plot(ccw_china$date, ccw_china$China, type="l", lwd=3, lty=3,
     ylab='',
     xlab='',
     xaxt="n",
     col=5,
     cex.axis=0.7,
     las=2,
     main = "COVID-19 cumulative cases in the US versus China",
     cex.main=0.9)

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

lines(ccw$date, ccw$US, lwd=3, col=4)

legend(ccw_china$date[1], 70000, legend=c("China", "US"),
       col=c(5, 4), lty=c(3,1), lwd=3, cex=0.8,
       box.lty=0)