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.
cc
a numeric vector containing the UN's country codes
yr
a numeric vector indicating the year of the data point
sex
a character vector
agegr
a numeric vector
scen2
a factor with levels BP
CEN
CER
FT_Singapore_TR
GET
UN
... different population projection scenarios - see References.
variable
a factor with levels e1
e2
e3
e4
value
a 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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