Count per year with only start and end year data - r

Question

I want to create a line chart in ggplot2 with 350 beer breweries. I want to count per year how many active breweries there are. I only have the start and end date of brewery activity. tidyverse answers prefered.
begin_datum_jaar is year the brewery started. eind_datum_jaar is in which year the brewery has ended.
example data frame:
library(tidyverse)
# A tibble: 4 x 3
brouwerijnaam begin_datum_jaar eind_datum_jaar
<chr> <int> <int>
1 Brand 1340 2019
2 Heineken 1592 2019
3 Grolsche 1615 2019
4 Bavaria 1719 2010
dput:
df <- structure(list(brouwerijnaam = c("Brand", "Heineken", "Grolsche",
"Bavaria"), begin_datum_jaar = c(1340L, 1592L, 1615L, 1719L),
eind_datum_jaar = c(2019L, 2019L, 2019L, 2010L)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -4L))
Desired output where etc. is a placeholder.
# A tibble: 13 x 2
year n
<chr> <dbl>
1 1340 1
2 1341 1
3 1342 1
4 1343 1
5 etc. 1
6 1592 2
7 1593 2
8 etc. 2
9 1625 3
10 1626 3
11 1627 3
12 1628 3
13 etc. 3

Answer 1

Could try:
library(tidyverse)
df %>%
rowwise %>%
do(data.frame(brouwerij = .$brouwerijnaam,
Year = seq(.$begin_datum_jaar, .$eind_datum_jaar, by = 1))) %>%
count(Year, name = "Active breweries") %>%
ggplot(aes(x = Year, y = `Active breweries`)) +
geom_line() +
theme_minimal()
Or try expand for the first part:
df %>%
group_by(brouwerijnaam) %>%
expand(Year = begin_datum_jaar:eind_datum_jaar) %>%
ungroup() %>%
count(Year, name = "Active breweries")
However, note that the rowwise, do or expand parts are resource intensive and may take long time. If that happens, I'd rather use data.table for expanding the data frame, and then continue, like below:
library(data.table)
library(tidyverse)
df <- setDT(df)[, .(Year = seq(begin_datum_jaar, eind_datum_jaar, by = 1)), by = brouwerijnaam]
df %>%
count(Year, name = "Active breweries") %>%
ggplot(aes(x = Year, y = `Active breweries`)) +
geom_line() +
theme_minimal()
The above gives you the plot directly. If you'd like to save it to a data frame first (and then do the ggplot2 thing), this is the main part (I use the data.table for expanding as it's much faster in my experience):
library(data.table)
library(tidyverse)
df <- setDT(df)[
, .(Year = seq(begin_datum_jaar, eind_datum_jaar, by = 1)),
by = brouwerijnaam] %>%
count(Year, name = "Active breweries")
Output:
# A tibble: 680 x 2
Year `Active breweries`
<dbl> <int>
1 1340 1
2 1341 1
3 1342 1
4 1343 1
5 1344 1
6 1345 1
7 1346 1
8 1347 1
9 1348 1
10 1349 1
# ... with 670 more rows

Answer 2

We can use map2 to get the sequence from start to end date for each corresponding element, unnest the list column to expand and use count to get the frequency of the 'year'
library(tidyverse)
df %>%
transmute(year = map2(begin_datum_jaar, eind_datum_jaar, `:`)) %>%
unnest %>%
count(year)
# A tibble: 680 x 2
# year n
# <int> <int>
# 1 1340 1
# 2 1341 1
# 3 1342 1
# 4 1343 1
# 5 1344 1
# 6 1345 1
# 7 1346 1
# 8 1347 1
# 9 1348 1
#10 1349 1
# … with 670 more rows
Or using Map from base R
table(unlist(do.call(Map, c(f = `:`, df[-1]))))

Answer 3

df1 <- data.frame(year=1000:2020) # Enter range for years of choice
df1 %>%
rowwise()%>%
mutate(cnt=nrow(df %>%
filter(begin_datum_jaar<year & eind_datum_jaar>year)
)
)