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e0Fproj80l <- read.delim(file='e0Fproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Fproj80l.R
|
e0Fproj80u <- read.delim(file='e0Fproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Fproj80u.R
|
e0Fproj95l <- read.delim(file='e0Fproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Fproj95l.R
|
e0Fproj95u <- read.delim(file='e0Fproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Fproj95u.R
|
e0M <- read.delim(file='e0M.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0M.R
|
e0M_supplemental <- read.delim(file='e0M_supplemental.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0M_supplemental.R
|
e0Mproj <- read.delim(file='e0Mproj.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Mproj.R
|
e0Mproj80l <- read.delim(file='e0Mproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Mproj80l.R
|
e0Mproj80u <- read.delim(file='e0Mproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Mproj80u.R
|
e0Mproj95l <- read.delim(file='e0Mproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Mproj95l.R
|
e0Mproj95u <- read.delim(file='e0Mproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/e0Mproj95u.R
|
migration <- read.delim(file='migration.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/migration.R
|
mxF <- read.delim(file='mxF.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/mxF.R
|
mxM <- read.delim(file='mxM.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/mxM.R
|
percentASFR <- read.delim(file='percentASFR.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/percentASFR.R
|
# This dataset is created on the fly as a sum of the age-specific population estimates popM and popF
pop <- local({
source('popM.R')
source('popF.R')
sum.by.country <- function(dataset) {
year.cols.idx <- grep('^[0-9]{4}', colnames(dataset))
plyr::ddply(dataset[,c(which(colnames(dataset)=='country_code'), year.cols.idx)],
"country_code", .fun = plyr::colwise(sum))
}
tpopM <- sum.by.country(popM)
tpopF <- sum.by.country(popF)
# The male and female dataset should be in the same format,
# i.e. the countries and years should be in the same order, but just to be sure
# match columns and rows. It will fail if there are different sets of countries
# in the two datasets.
cols.to.sumM <- colnames(tpopM)[-match('country_code', colnames(tpopM))]
cols.to.sumF <- colnames(tpopF)[-match('country_code', colnames(tpopF))]
cols.to.sumF.idx <- match(cols.to.sumF, cols.to.sumM)
rowsF.idx <- match(tpopF$country_code, tpopM$country_code)
name.col <- grep('^name$|^country$', colnames(popM), value=TRUE)
cbind(country_code=tpopM$country_code, name=popM[,name.col][match(tpopM$country_code, popM$country_code)],
tpopM[,cols.to.sumM] + tpopF[rowsF.idx, cols.to.sumF[cols.to.sumF.idx]])
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/pop.R
|
popF <- read.delim(file='popF.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popF.R
|
popFprojHigh <- read.delim(file='popFprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popFprojHigh.R
|
popFprojLow <- read.delim(file='popFprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popFprojLow.R
|
popFprojMed <- read.delim(file='popFprojMed.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popFprojMed.R
|
popM <- read.delim(file='popM.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popM.R
|
popMprojHigh <- read.delim(file='popMprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popMprojHigh.R
|
popMprojLow <- read.delim(file='popMprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popMprojLow.R
|
popMprojMed <- read.delim(file='popMprojMed.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popMprojMed.R
|
# This dataset is created on the fly as a sum of the age-specific population median projections popMprojMed and popFprojMed
popproj <- local({
source('popMprojMed.R')
source('popFprojMed.R')
sum.by.country <- function(dataset) {
year.cols.idx <- grep('^[0-9]{4}', colnames(dataset))
plyr::ddply(dataset[,c(which(colnames(dataset)=='country_code'), year.cols.idx)],
"country_code", .fun = plyr::colwise(sum))
}
tpopM <- sum.by.country(popMprojMed)
tpopF <- sum.by.country(popFprojMed)
# The male and female dataset should be in the same format,
# i.e. the countries and years should be in the same order, but just to be sure
# match columns and rows. It will fail if there are different sets of countries
# in the two datasets.
cols.to.sumM <- colnames(tpopM)[-match('country_code', colnames(tpopM))]
cols.to.sumF <- colnames(tpopF)[-match('country_code', colnames(tpopF))]
cols.to.sumF.idx <- match(cols.to.sumF, cols.to.sumM)
rowsF.idx <- match(tpopF$country_code, tpopM$country_code)
name.col <- grep('^name$|^country$', colnames(popMprojMed), value=TRUE)
cbind(country_code=tpopM$country_code,
name=popMprojMed[,name.col][match(tpopM$country_code, popMprojMed$country_code)],
tpopM[,cols.to.sumM] + tpopF[rowsF.idx, cols.to.sumF[cols.to.sumF.idx]])
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popproj.R
|
popproj80l <- read.delim(file='popproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popproj80l.R
|
popproj80u <- read.delim(file='popproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popproj80u.R
|
popproj95l <- read.delim(file='popproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popproj95l.R
|
popproj95u <- read.delim(file='popproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popproj95u.R
|
popprojHigh <- read.delim(file='popprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popprojHigh.R
|
popprojLow <- read.delim(file='popprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/popprojLow.R
|
sexRatio <- read.delim(file='sexRatio.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/sexRatio.R
|
tfr <- read.delim(file='tfr.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfr.R
|
tfr_supplemental <- read.delim(file='tfr_supplemental.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfr_supplemental.R
|
tfrproj80l <- read.delim(file='tfrproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrproj80l.R
|
tfrproj80u <- read.delim(file='tfrproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrproj80u.R
|
tfrproj95l <- read.delim(file='tfrproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrproj95l.R
|
tfrproj95u <- read.delim(file='tfrproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrproj95u.R
|
tfrprojHigh <- read.delim(file='tfrprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrprojHigh.R
|
tfrprojLow <- read.delim(file='tfrprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrprojLow.R
|
tfrprojMed <- read.delim(file='tfrprojMed.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2015/data/tfrprojMed.R
|
.onLoad <- function (lib, pkg) {
suppressPackageStartupMessages(requireNamespace("data.table"))
}
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/R/zzz.R
|
UNlocations <- read.delim(file='UNlocations.txt', comment.char='#')
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/UNlocations.R
|
e0F <- read.delim(file='e0F.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0F.R
|
e0F_supplemental <- read.delim(file='e0F_supplemental.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0F_supplemental.R
|
e0Fproj <- read.delim(file='e0Fproj.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Fproj.R
|
e0Fproj80l <- read.delim(file='e0Fproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Fproj80l.R
|
e0Fproj80u <- read.delim(file='e0Fproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Fproj80u.R
|
e0Fproj95l <- read.delim(file='e0Fproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Fproj95l.R
|
e0Fproj95u <- read.delim(file='e0Fproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Fproj95u.R
|
e0M <- read.delim(file='e0M.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0M.R
|
e0M_supplemental <- read.delim(file='e0M_supplemental.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0M_supplemental.R
|
e0Mproj <- read.delim(file='e0Mproj.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Mproj.R
|
e0Mproj80l <- read.delim(file='e0Mproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Mproj80l.R
|
e0Mproj80u <- read.delim(file='e0Mproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Mproj80u.R
|
e0Mproj95l <- read.delim(file='e0Mproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Mproj95l.R
|
e0Mproj95u <- read.delim(file='e0Mproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/e0Mproj95u.R
|
migration <- read.delim(file='migration.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/migration.R
|
mxF <- read.delim(file='mxF.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/mxF.R
|
mxM <- read.delim(file='mxM.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/mxM.R
|
percentASFR <- read.delim(file='percentASFR.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/percentASFR.R
|
# Total population (observed)
# This dataset is created on the fly as a sum of the sex-specific population estimates popMT and popFT
pop <- local({
source('popMT.R')
source('popFT.R')
# The male and female dataset should be in the same format,
# i.e. the countries and years should be in the same order, but just to be sure
# match columns and rows. It will fail if there are different sets of countries
# in the two datasets.
cols.to.sumM <- colnames(popMT)[-match(c('country_code', "name"), colnames(popMT))]
cols.to.sumF <- colnames(popFT)[-match(c('country_code', "name"), colnames(popFT))]
cols.to.sumF.idx <- match(cols.to.sumF, cols.to.sumM)
rowsF.idx <- match(popFT$country_code, popMT$country_code)
cbind(country_code=popMT$country_code, name=popMT[,"name"],
popMT[,cols.to.sumM] + popFT[rowsF.idx, cols.to.sumF[cols.to.sumF.idx]])
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/pop.R
|
popF <- read.delim(file='popF.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popF.R
|
# Total female population (observed)
# This dataset is created on the fly as a sum of the age-specific population estimates popF
popFT <- local({
source('popF.R')
sum.by.country <- function(dataset) {
year.cols <- grep('^[0-9]{4}', colnames(dataset), value = TRUE)
name.col <- grep('^name$|^country$', colnames(dataset), value=TRUE)
data.table::setnames(dataset, name.col, "name") # rename if necessary
dataset[, c("country_code", "name", year.cols),
with = FALSE][,lapply(.SD, sum, na.rm = TRUE),
by = c("country_code", "name")]
}
as.data.frame(sum.by.country(data.table::as.data.table(popF)))
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popFT.R
|
# Total female population (projection median)
# This dataset is created on the fly as a sum of the age-specific population median projections popFprojMed
popFTproj <- local({
source('popFprojMed.R')
sum.by.country <- function(dataset) {
year.cols <- grep('^[0-9]{4}', colnames(dataset), value = TRUE)
name.col <- grep('^name$|^country$', colnames(dataset), value=TRUE)
data.table::setnames(dataset, name.col, "name") # rename if necessary
dataset[, c("country_code", "name", year.cols),
with = FALSE][,lapply(.SD, sum, na.rm = TRUE),
by = c("country_code", "name")]
}
as.data.frame(sum.by.country(data.table::as.data.table(popFprojMed)))
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popFTproj.R
|
popFprojHigh <- read.delim(file='popFprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popFprojHigh.R
|
popFprojLow <- read.delim(file='popFprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popFprojLow.R
|
popFprojMed <- read.delim(file='popFprojMed.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popFprojMed.R
|
popM <- read.delim(file='popM.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popM.R
|
# Total male population (observed)
# This dataset is created on the fly as a sum of the age-specific population estimates popM
popMT <- local({
source('popM.R')
#suppressPackageStartupMessages(library(data.table))
sum.by.country <- function(dataset) {
year.cols <- grep('^[0-9]{4}', colnames(dataset), value = TRUE)
name.col <- grep('^name$|^country$', colnames(dataset), value=TRUE)
data.table::setnames(dataset, name.col, "name") # rename if necessary
dataset[, c("country_code", "name", year.cols),
with = FALSE][,lapply(.SD, sum, na.rm = TRUE),
by = c("country_code", "name")]
}
as.data.frame(sum.by.country(data.table::as.data.table(popM)))
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popMT.R
|
# Total male population (projection median)
# This dataset is created on the fly as a sum of the age-specific population median projections popMprojMed
popMTproj <- local({
source('popMprojMed.R')
sum.by.country <- function(dataset) {
year.cols <- grep('^[0-9]{4}', colnames(dataset), value = TRUE)
name.col <- grep('^name$|^country$', colnames(dataset), value=TRUE)
data.table::setnames(dataset, name.col, "name") # rename if necessary
dataset[, c("country_code", "name", year.cols),
with = FALSE][,lapply(.SD, sum, na.rm = TRUE),
by = c("country_code", "name")]
}
as.data.frame(sum.by.country(data.table::as.data.table(popMprojMed)))
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popMTproj.R
|
popMprojHigh <- read.delim(file='popMprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popMprojHigh.R
|
popMprojLow <- read.delim(file='popMprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popMprojLow.R
|
popMprojMed <- read.delim(file='popMprojMed.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popMprojMed.R
|
# Total population (projection median)
# This dataset is created on the fly as a sum of the sex-specific population median projections popMTproj and popFTproj
popproj <- local({
source('popMTproj.R')
source('popFTproj.R')
# The male and female dataset should be in the same format,
# i.e. the countries and years should be in the same order, but just to be sure
# match columns and rows. It will fail if there are different sets of countries
# in the two datasets.
tpopM <- popMTproj
tpopF <- popFTproj
cols.to.sumM <- colnames(tpopM)[-match(c('country_code', "name"), colnames(tpopM))]
cols.to.sumF <- colnames(tpopF)[-match(c('country_code', "name"), colnames(tpopF))]
cols.to.sumF.idx <- match(cols.to.sumF, cols.to.sumM)
rowsF.idx <- match(tpopF$country_code, tpopM$country_code)
cbind(country_code=tpopM$country_code,
name=tpopM[,"name"],
tpopM[,cols.to.sumM] + tpopF[rowsF.idx, cols.to.sumF[cols.to.sumF.idx]])
})
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popproj.R
|
popproj80l <- read.delim(file='popproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popproj80l.R
|
popproj80u <- read.delim(file='popproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popproj80u.R
|
popproj95l <- read.delim(file='popproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popproj95l.R
|
popproj95u <- read.delim(file='popproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popproj95u.R
|
popprojHigh <- read.delim(file='popprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popprojHigh.R
|
popprojLow <- read.delim(file='popprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/popprojLow.R
|
sexRatio <- read.delim(file='sexRatio.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/sexRatio.R
|
tfr <- read.delim(file='tfr.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfr.R
|
tfr_supplemental <- read.delim(file='tfr_supplemental.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfr_supplemental.R
|
tfrproj80l <- read.delim(file='tfrproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrproj80l.R
|
tfrproj80u <- read.delim(file='tfrproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrproj80u.R
|
tfrproj95l <- read.delim(file='tfrproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrproj95l.R
|
tfrproj95u <- read.delim(file='tfrproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrproj95u.R
|
tfrprojHigh <- read.delim(file='tfrprojHigh.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrprojHigh.R
|
tfrprojLow <- read.delim(file='tfrprojLow.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrprojLow.R
|
tfrprojMed <- read.delim(file='tfrprojMed.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2017/data/tfrprojMed.R
|
UNlocations <- read.delim(file='UNlocations.txt', comment.char='#')
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/UNlocations.R
|
e0F <- read.delim(file='e0F.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0F.R
|
e0F_supplemental <- read.delim(file='e0F_supplemental.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0F_supplemental.R
|
e0Fproj <- read.delim(file='e0Fproj.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0Fproj.R
|
e0Fproj80l <- read.delim(file='e0Fproj80l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0Fproj80l.R
|
e0Fproj80u <- read.delim(file='e0Fproj80u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0Fproj80u.R
|
e0Fproj95l <- read.delim(file='e0Fproj95l.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0Fproj95l.R
|
e0Fproj95u <- read.delim(file='e0Fproj95u.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0Fproj95u.R
|
e0M <- read.delim(file='e0M.txt', comment.char='#', check.names=FALSE)
|
/scratch/gouwar.j/cran-all/cranData/wpp2019/data/e0M.R
|
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