Find out if time periods of years overlap - r

Question

I have a dataframe that lists political mandates with their start and end year. The question I want to answer is "How many people (person_id) have had mandates that overlap in terms of years active?
I've tried sequencing the active years as vectors, and then grouping and summarising by intersecting the vectors of active years.
My input table
id
person_id
start_year
end_year
1
6
1987
1992
2
6
1989
1995
mandates_active <- mandates %>% mutate(active_years = map2(mandate_start_year, mandate_end_year, seq))
I get an additional column with the sequenced active years:
id
person_id
start_year
end_year
active_years
1
6
1987
1992
[1987, 1988, 1989 ...]
2
6
1989
1995
[1989, 1990, 1991 ...]
Then I try to group this bz person_id and summarise by intersecting the active years list, but I need two arguments for the intersect function, hence this doesn't work:
mandates_test <- mandates_active %>% group_by(person_id) %>% summarise(intersect(active_years))
My output would show which person_ids have had multiple mandates during overlapping years.

Answer 1

Maybe this works for you. It shows the person_id and the overlapping years in the final result.
data.frame(df %>%
rowwise() %>%
summarize(id, person_id, f = seq(start_year, end_year, 1)) %>%
group_by(person_id) %>%
summarize(overlapping_years = list(f[duplicated(f)])))
person_id overlapping_years
1 6 1989, 1990, 1991, 1992
2 7
3 8 1992
If you just want a sum of years
df %>%
rowwise() %>%
summarize(id, person_id, f = seq(start_year, end_year, 1)) %>%
group_by(person_id) %>%
summarize(overlapping_years = length(f[duplicated(f)]))
# A tibble: 3 × 2
person_id overlapping_years
<dbl> <int>
1 6 4
2 7 0
3 8 1
Extended Data
df <- structure(list(id = c(1L, 2L, 1L, 2L, 1L, 2L), person_id = c(6,
6, 7, 7, 8, 8), start_year = c(1987, 1989, 1987, 1993, 1987,
1992), end_year = c(1992L, 1995L, 1992L, 1995L, 1992L, 1995L)), row.names = c(NA,
6L), class = "data.frame")

Answer 2

library(dplyr)
library(tidyr)
set.seed(123)
#Data example
start_year <- sample(1957:2003, 12, T)
end_year <- start_year + sample(1:4, 12,T)
data <- data.frame(person_id = 1:12, start_year, end_year)
data
#> person_id start_year end_year
#> 1 1 1987 1990
#> 2 2 1971 1974
#> 3 3 1970 1971
#> 4 4 1959 1963
#> 5 5 1998 1999
#> 6 6 1999 2000
#> 7 7 1993 1994
#> 8 8 1970 1973
#> 9 9 1981 1985
#> 10 10 1982 1984
#> 11 11 1983 1986
#> 12 12 1961 1963
# Unroll the intervals into registers:
pers_years <- data %>% rowwise() %>%
mutate(years = list(start_year:end_year)) %>%
unnest(years)
Number of distinct persons by year:
summarise(persons = n_distinct(person_id))
#> # A tibble: 25 × 2
#> years persons
#> <int> <int>
#> 1 1959 1
#> 2 1960 1
#> 3 1961 2
#> 4 1962 2
#> 5 1963 2
#> 6 1970 2
#> 7 1971 3
#> 8 1972 2
#> 9 1973 2
#> 10 1974 1
#> # … with 15 more rows
Number of distinct persons that have mandates that overlaps with at least other person in the dataset:
pers_years %>%
inner_join(
pers_years %>% group_by(years) %>%
summarise(persons = n_distinct(person_id)) %>%
filter(persons > 1),
by = "years") %>%
summarise(n_persons = n_distinct(person_id))
#> # A tibble: 1 × 1
#> n_persons
#> <int>
#> 1 10