Gender balance in R

Nice graph, Scott, thanks!

Based on your code I plotted not the absolute numbers but the ratios, 
which show slowly increasing relative participation of female Rhelpers 
over time (red = women, blue=men, black=unknown). After a c. 5% female 
contribution in 1998, this has grown to about 15% now. At this rate 
we'll reach parity around AD 2080.

My code:

if (!require(gender)) {
library(devtools)
install_github("scottkosty/gender")
library(gender)
}
rHelp <- rHelpNames
rHelp[is.na(rHelp$gender), "gender"] <- "unknown"

yr <- unique(rHelp$year)

helpers <- list(dates, M=rep(0, length(yr)), F=rep(0, length(yr)), 
unkn=rep(0, length(yr)))

for(i in 1:nrow(rHelp))
  {
   j <- which(yr == rHelp$year[i])
   gender <- rHelp$gender[i]
   if(gender == "M")
    helpers$M[[j]] <- helpers$M[[j]]+1 else
     if(gender == "F")
      helpers$F[[j]] <- helpers$F[[j]]+1 else
       if(gender == "unknown")
        helpers$unkn[[j]] <- helpers$unkn[[j]]+1
  }
plot(yr, helpers$M / (helpers$M+helpers$F+helpers$unkn), type="l", 
col=4, ylim=c(0,1), ylab="proportions", yaxs="i")
lines(yr, helpers$F / (helpers$M+helpers$F+helpers$unkn), col=2) 

lines(yr, helpers$unkn / (helpers$M+helpers$F+helpers$unkn))

Cheers,

Maarten

Gender balance in R

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