wpp.indicator(what, ...)tfr and tfrprojMed.e0F and e0Fproj.
e0M and e0Mproj.
popF and popFprojMed and aggregates over ages.
popM and popMprojMed and aggregates over ages.
migration is used. For wpp2012 and wpp2010 it aggregates datasets migrationF and migrationM over ages.
popM and popMprojMed. It requires two arguments in ..., namely sexm=c("F", "M") and agem=c("0-4", "5-9", ..., "95-99", "100+"). The function aggregates population counts over the given sex and age groups.
mxF and mxM. It requires two atguments in ..., namely sex which is either "F" or "M", and age which is one of ("0", "1", "5", "10", "15", "20", ... "95", "100+").
tfr and tfrprojMed which are merged together and dataset percentASFR to derive age-specific rates. It requires one argument in ..., namely age which is one of ("15-19", "20-24", ..., "45-49").
percentASFR. Argument agem as defined above giving one or more age categories is required.
sexRatio.
which.pi which is one of 80, 95, half.child, and an argument bound which is
either low or high. Arguments sexm and agem (as defined above, but of length one) are required for popagesex.ci.
charcode (alpha-2 ISO 3166 country code), Year, and value.wpp.by.country, wpp.by.year
tfr <- wpp.indicator("fert")
## Not run:
# # Histogram of TFR
# print(qplot(value, data=tfr) + facet_wrap(~ Year))## End(Not run)
## Not run:
# mxM01 <- wpp.indicator("mortagesex", sex="M", age="0")
# # Plot map
# plot(gvisGeoMap(tfr, locationvar='charcode', numvar='value'))## End(Not run)
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