Plotting cumulative counts in ggplot2

Question

There are some posts about plotting cumulative densities in ggplot. I\'m currently using the accepted answer from Easier way to plot the cumulative frequency distribution in

Answer 1

You can apply row_number over the groups, and utilize that as the Y aesthetic in a geom_step or other geometry. You'll just have to sort by X, or the values will appear as they do in the data frame, unordered.

ggplot(x %>% 
         group_by(A) %>% 
         arrange(X) %>% 
         mutate(rn = row_number())) + 
  geom_step(aes(x=X, y=rn, color=A))

Answer 2

This will not solve directly problem with grouping of lines but it will be workaround.

You can add three calls to stat_bin() where you subset your data according to A levels.

ggplot(x,aes(x=X,color=A)) +
  stat_bin(data=subset(x,A=="a"),aes(y=cumsum(..count..)),geom="step")+
  stat_bin(data=subset(x,A=="b"),aes(y=cumsum(..count..)),geom="step")+
  stat_bin(data=subset(x,A=="c"),aes(y=cumsum(..count..)),geom="step")

UPDATE - solution using geom_step()

Another possibility is to multiply values of ..y.. with number of observations in each level. To get this number of observations at this moment only way I found is to precalculate them before plotting and add them to original data frame. I named this column len. Then in geom_step() inside aes() you should define that you will use variable len=len and then define y values as y=..y.. * len.

set.seed(123)
x <- data.frame(A=replicate(200,sample(c("a","b","c"),1)),X=rnorm(200))
library(plyr)
df <- ddply(x,.(A),transform,len=length(X))
ggplot(df,aes(x=X,color=A)) + geom_step(aes(len=len,y=..y.. * len),stat="ecdf")