Culmulative count of discrete variable in ggplot2

Question

This is related to Plotting cumulative counts in ggplot2 , but that question was dealing with a continuous variable (rather than discrete).

Here, I have a bar chart

set.seed(2021)
dat <- data.frame(x = c(rpois(100, 1), 7, 10))
ggplot(dat) + geom_bar(aes(x, ..count..))

I'm trying to plot a cumulative count with

ggplot(dat) + geom_bar(aes(x, cumsum(..count..)))

There are gaps when there are 'missing values' (ie when x is 5, 6, 7, 9).

Is there a quick and easy way to have a bar chart with gaps filled with bars , ie I will have 11 bars? I could have manually created a data frame with the cumulative counts and plot it as usual, but I'm curious if there's a more elegant way.

Answer 1

You can convert the variable to a factor when plotting.

ggplot(dat) + geom_bar(aes(factor(x), cumsum(..count..)))

Answer 2

I would not call this an "easy" approach but the only one I could come up with so solve your question:

1. Pre-summarise your dataset using eg dplyr::count

2. Fill up your dataset with the missing categories using eg tidyr::complete (To this end I first convert x to a factor).

3. Plot via geom_col

library(ggplot2)
library(dplyr)
library(tidyr)

set.seed(2021)
dat <- data.frame(x = c(rpois(100, 1), 7, 10))
dat <- dat %>% 
  count(x) %>% 
  mutate(x = factor(x, levels = seq(range(x)[1], range(x)[2], by = 1))) %>% 
  tidyr::complete(x, fill = list(n = 0))

ggplot(dat) + geom_col(aes(x, cumsum(n)))

Answer 3

If you'll use stat_bin instead of geom_bar may be that can help..

ggplot(dat) + stat_bin(aes(x, cumsum(..count..)))