It is time for women to stop being politely angry (Leymah Gbowee, Nobel Prize Peace Winner)
Sometimes very simple plots give insight into we live in a world of differences. This plot shows the mean age at marriage for men and women across countries:
Being a woman in some countries of this world must be a hard experience:
#Singulate mean age at marriage: http://data.un.org/Data.aspx?d=GenderStat&f=inID%3a20 #Population: http://data.un.org/Data.aspx?d=SOWC&f=inID%3a105 require("sqldf") require("ggplot2") setwd("YOUR WORKING DIRECTORY HERE") mar=read.csv("UNdata_Export_20150309_171525152.csv", nrows=321, header=T, row.names=NULL) pop=read.csv("UNdata_Export_20150309_172046384.csv", nrows=999, header=T, row.names=NULL) colnames(mar)="Country" colnames(pop)="Country" data=sqldf("SELECT a.Country, a.Value as Pop, b.Value as Female, c.Value as Male FROM pop a INNER JOIN mar b ON (a.Country=b.Country AND b.Subgroup='Female') INNER JOIN mar c ON (a.Country=c.Country AND c.Subgroup='Male') WHERE a.Subgroup = 'Total'") opts=theme( panel.background = element_rect(fill="gray98"), panel.border = element_rect(colour="black", fill=NA), axis.line = element_line(size = 0.5, colour = "black"), axis.ticks = element_line(colour="black"), panel.grid.major = element_line(colour="gray75", linetype = 2), panel.grid.minor = element_blank(), axis.text = element_text(colour="gray25", size=15), axis.title = element_text(size=18, colour="gray10"), legend.key = element_blank(), legend.position = "none", legend.background = element_blank(), plot.title = element_text(size = 40, colour="gray10")) ggplot(data, aes(x=Female, y=Male, size=log(Pop), label=Country), guide=FALSE)+ geom_point(colour="white", fill="chartreuse3", shape=21, alpha=.55)+ scale_size_continuous(range=c(2,36))+ scale_x_continuous(limits=c(16,36), breaks=seq(16, 36, by = 2), expand = c(0, 0))+ scale_y_continuous(limits=c(16,36), breaks=seq(16, 36, by = 2), expand = c(0, 0))+ geom_abline(intercept = 0, slope = 1, colour = "gray10", linetype=2)+ labs(title="The World We Live In #4: Marriage Ages", x="Females mean age at marriage", y="Males mean age at marriage")+ geom_text(data=subset(data, abs(Female-Male)>7), size=5.5, colour="gray25", hjust=0, vjust=0)+ geom_text(data=subset(data, Female>=32|Female<=18), size=5.5, colour="gray25", hjust=0, vjust=0)+ geom_text(aes(24, 17), colour="gray25", hjust=0, label="Source: United Nations (size of bubble depending on population)", size=5)+opts
3 thoughts on “The World We Live In #4: Marriage Ages”
I feel that this graph is problematic. This particular graph is hiding most of the reality behind its measure of center. There is no sense of the underlying distributions; their spread, their modality, the structure of co-association.
Each country will tend to sprawl across the entire graph. Resolving that is tricky.
We need some creative ideas…
Fist of all, I love this creative idea of aschinchon
I try to make it better here https://rain1024.shinyapps.io/dataR/1-interactive.Rmd
I use googleVis and group countries by convinent.
Good job! Thanks for your comment!