library(survival)
library(ggplot2)
data(lung)
s <- survfit(Surv(time, status) ~ 1, data = lung)
dat <- data.frame(time = c(0, s$time),
                  surv = c(1, s$surv),
                  nr = c(s$n, s$n.risk))
pl1 <- ggplot(dat, aes(time, surv)) + geom_step()

pl2 <- ggplot(dat, aes(time, nr)) + geom_area()

library(reshape2)
dat.long<-melt(dat,id.vars="time")
head(dat.long)
  time variable     value
1    0     surv 1.0000000
2    5     surv 0.9956140
3   11     surv 0.9824561
4   12     surv 0.9780702
5   13     surv 0.9692982
6   15     surv 0.9649123

ggplot()+geom_step(data=subset(dat.long,variable=="surv"),aes(time,value))+
  geom_area(data=subset(dat.long,variable=="nr"),aes(time,value))+
  facet_grid(variable~.,scales="free_y")