Description Usage Format Source References Examples
Reconstruction of populations by age, sex and highest level of educational attainment for 142 countries for 1970-2000 using demographic back-projection methods together with education forward projections for 2000-2050.
1 |
A data frame with 1009152 observations on the following 7 variables.
cca numeric vector containing the UN's country codes
yra numeric vector indicating the year of the data point
sexa character vector
agegra numeric vector
scen2a factor with levels BP CEN CER FT_Singapore_TR GET UN
... different population projection scenarios - see References.
variablea factor with levels e1 e2 e3 e4
valuea numeric vector
... the number of people in the respective country, year, by sex, age, and educational attainment level
http://www.iiasa.ac.at/Research/POP/edu07/index.html
Lutz, W., A. Goujon, S. KC, and W. Sanderson. 2007. Reconstruction of populations by age, sex and level of educational attainment for 120 countries for 1970-2000. Vienna Yearbook of Population Research 2007:193-235.\
KC, S., B. Barakat, A. Goujon, V. Skirbekk, and W. Lutz. 2010. Projection of populations by level of educational attainment, age, and sex for 120 countries for 2005-2050. Demographic Research 22:383-472.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | library(reshape)
data(EduDat)
data(dictionary)
icountry <- "China"
ipop <- subset(EduDat,cc==getcode(icountry,dictionary) & scen2 != "BP")
ipop <- cast(ipop,yr~scen2,sum)
row.names(ipop) <- ipop[,1]
matplot(as.data.frame(ipop[,-1]),type="l",lwd=3,main=paste("Projected Population 15+ by Education Scenario, ",icountry,sep=""),cex.main=1.8,
xlab="Year",ylab="Total Population in 1000s",xaxt="n",cex=1.5,cex.axis=1.5,cex.lab=1.5)
axis(1,at=1:nrow(ipop),labels=row.names(ipop),cex.axis=1.5)
grid(lwd=2,lty=2)
legend(legend=names(ipop[,-1]),title="Education Scenario: ",
col=1:ncol(ipop[,-1]),lwd=3,lty=1:ncol(ipop[,-1]),
"topleft",inset=c(0.02,0.02),bty="o",bg="grey",cex=1.5)
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