Say I have this example data frame
set.seed(12345)
n1 <- 3
n2 <- 10
n3 <- 60
times <- seq(0, 100, 0.5)
individual <- c(rep(1, n1),
df$step <- 1
library(plyr)
df <- ddply(df,.(individual),transform,step=cumsum(step))
plot(step~events,data=df[df$individual==1,],type="s",xlim=c(0,max(df$events)),ylim=c(0,max(df$step)),xlab="time",ylab="step")
lines(step~events,data=df[df$individual==2,],type="s",col=2)
lines(step~events,data=df[df$individual==3,],type="s",col=3)
There is also the stepfun
function in the stats package. Using that, you could use the plot
method for that object class:
sdf <- split(df, individual)
plot(1, 1, type = "n", xlim = c(0, max(events)), ylim = c(0, max(table(individual))),
ylab = "step", xlab = "time")
sfun <- lapply(sdf, function(x){
sf <- stepfun(sort(x$events), seq_len(nrow(x) + 1) - 1)
plot(sf, add = TRUE, col = unique(x$individual), do.points = FALSE)
})
Use ggplot2
:
library(ggplot2)
# Add step height information with sequence and rle
df$step <- sequence(rle(df$individual)$lengths)
# plot
df$individual <- factor(df$individual)
ggplot(df, aes(x=events, group=individual, colour=individual, y=step)) +
geom_step()