Example code for https://aksela.wordpress.com/2018/07/17/stratified-sampling-partitioning-with-continuous-control-variable/

Stratified partitioning 1.r

shootings <- structure(list(Year = 1982:2017, Fatalities = c(8, 
0, 28, 0, 15, 6, 7, 15, 10, 35, 9, 23, 5, 6, 6, 9, 14, 42, 7, 
5, 0, 7, 5, 17, 21, 53, 17, 39, 9, 19, 71, 35, 15, 37, 65, 99
)), row.names = c(NA, 36L), class = "data.frame")

Stratified partitioning 2.r

library(caret)

set.seed(1)
k <- 5

yeargroups <- cut(shootings[,1], nrow(shootings)/k)
shootings$Fold <- createFolds(yeargroups, k, list=FALSE)
head(shootings)

#   Year Fatalities Fold
# 1 1982          8    3
# 2 1983          0    2
# 3 1984         28    4
# 4 1985          0    1
# 5 1986         15    2
# 6 1987          6    5

Stratified partitioning 3.r

par(mar=c(3, 3, 1, 1), mgp=c(1.8, 0.6, 0))
plot(shootings[1:2], col=rainbow(k)[shootings$Fold], pch=16, cex=1.5)

aggregate(Year ~ Fold, shootings, mean)
#   Fold     Year
# 1    1 2000.286
# 2    2 1998.125
# 3    3 1999.571
# 4    4 1999.286
# 5    5 2000.429

Stratified partitioning 4.r

ll <- list()
ngroups <- 1:15

for (i in ngroups) {
    lli <- replicate(200, {
        if (i > 1) {
            yeargroups <- cut(shootings[,1], i)
        } else {
            yeargroups <- shootings[,1]
        }
        
        shootings$Fold <- createFolds(yeargroups, k, list=FALSE)
        a <- aggregate(Year ~ Fold, shootings, mean)[,2]
    
        round(diff(range(a)), 4)
    })
    ll[[i]] <- lli
}

ll.mat <- simplify2array(ll)

par(xaxs="i")
matplot(ngroups, t(ll.mat), type="l", lty=1, lwd=0.2, col="#00000044",
  xaxt="n", xlab="Number of strata", ylab="Max absolute difference")
lines(ngroups, apply(ll.mat, 2, mean), col="#2078FA", lwd=4)
axis(1, at=ngroups)
legend("topleft", legend="Mean", bty="n", lwd=4, col="#2078FA")
quartz.save("nstrat.png", dpi=110)