if (!require(wpp2019)) { install.packages("wpp2019", dep=TRUE); library(wpp2019) } data(popM) data(popF) data(tfr) CNTRY <- c("Angola", "France", "Cameroon", "Nigeria", "China", "India", "Indonesia", "Japan", "Singapore", "Canada", "Malaysia", "Cambodia", "Pakistan", "Sudan", "Ghana", "Egypt", "Jordan") CNTRYn <- as.character(subset(tfr, name %in% CNTRY)$name) # For all countries/regions # CNTRYn <- as.character(tfr$name) TFRs <- subset(tfr, name %in% CNTRYn)[, '2015-2020'] CWRs <- numeric(length(CNTRYn)) for (i in 1:length(CNTRYn)) { M <- subset(popM, name==CNTRYn[i])[, '2015'] F <- subset(popF, name==CNTRYn[i])[, '2015'] CWRs[i] <- (M[1]+F[1])/sum(F[4:9]) # If up to 49 years old are included, denominator is sum(F[4:10]) } plot(CWRs, TFRs, pch=16, type="p", xlim=c(0,1)) text(CWRs, TFRs, CNTRYn, pos=4)