Cumulative stacked bar plot with the same variable with ggplot2 - r

Question

I got a data frame producers with two colums: person_id and year.
# A tibble: 3,207 x 2
person_id year
<chr> <chr>
1 GASH1991-04-30 2020
2 LOSP1969-06-29 2020
3 CRGM1989-08-26 2020
4 CEVE1954-07-15 2020
5 HERR1998-01-06 2020
6 TOLR1951-04-09 2020
7 BEAM1953-09-07 2020
8 ANRJ1977-07-06 2020
9 PAMH1982-02-06 2020
10 AKTE1967-11-15 2020
# ... with 3,197 more rows
I can summarise this dataframe to obtain cumulative sum:
producers %>%
select(person_id, year) %>%
group_by(year) %>%
distinct(person_id) %>%
summarise(total = n()) %>%
ungroup() %>%
mutate(cum = cumsum(total))
# A tibble: 3 x 3
year total cum
<chr> <int> <int>
1 2019 456 456
2 2020 1832 2288
3 2021 160 2448
An I can make a cummulative bar plot like this:
ggplot(producers, aes(x = as.factor(year), y = as.integer(cum))) +
geom_bar(position = "stack", stat = "identity") +
ylim(0,3000) +
xlab("Year") +
ylab("Producers") +
theme_classic()
But what I really want is something like this:
I've been trying with aes(fill = year) and other arguments but I can't get it. Thanks for your responses.

Answer 1

Here's an approach. Ultimately, we'll need two "year" variables, one to mark the category within each stack, and one to mark which stack we want it to appear in. Here, I set up year2 for the 2nd one, and filter out the values that shouldn't appear yet in each stack.
df2 <- data.frame(
year = 2019:2021,
total = c(456, 1832, 160)
)
library(tidyverse)
df2 %>%
crossing(year2 = df2$year) %>% # make copy for each year
filter(year <= year2) %>% # keep just the years up to current year
ggplot(aes(year2, total, fill = fct_rev(as.factor(year)))) +
geom_col() +
scale_fill_discrete(name = "Year")

Answer 2

ggplot2 works best with data in a long format where you have one variable to plot and then various identifying variables to control the fill, color, and facetting. Here I explicitly build a repeated data frame using map_dfr which essentially is running a for loop for each year in the input dataset. In dat_long the new column yearid becomes the x-axis identifier so within 2021 we can access the data for year 2019 through 2021 to control the color fill.
library(ggplot2)
library(dplyr)
library(purrr)
library(forcats)
year = c(2019, 2020, 2021)
sum = c(456, 1832, 160)
cumsum = c(456, 2288, 2448)
dat <- data.frame(year, sum)
# note: don't need the cumsum column
# instead, create long, replicated data where we repeat
# each years entry for every year that comes after it
dat_long <-
map_dfr(unique(dat$year),
~filter(dat, year <= .x) %>%
mutate(yearid = .x))
ggplot(data = dat_long,
aes(x = yearid,
y = sum,
# note: use factor to get discrete color palette, fct_rev to stack 2021 on top
fill = fct_rev(factor(year)))) +
geom_col()