I have a table and I want to get the cumulative sum within a group(by ID), but the cumulative count should reset if the counter is 0 at any point within a group and again start the cumulative count from 1.
ID Counter Cumulative
A 1 1
A 0 0
A 1 1
A 1 2
B 1 1
B 0 0
B 1 1
Create a temporary group column to create a new group everytime you encounter a 0.
library(dplyr)
df %>%
group_by(ID, grp = cumsum(Counter == 0)) %>%
mutate(Cumulative = cumsum(Counter)) %>%
ungroup() %>%
select(-grp) -> result
result
# ID Counter Cumulative
# <chr> <int> <int>
#1 A 1 1
#2 A 0 0
#3 A 1 1
#4 A 1 2
#5 B 1 1
#6 B 0 0
#7 B 1 1
The same logic can be implemented in base R and data.table as :
df$Cumulative <- with(df, ave(Counter, ID, cumsum(Counter == 0), FUN = cumsum))
library(data.table)
setDT(df)[, Cumulative := cumsum(Counter), .(ID, cumsum(Counter == 0))]
data
df <- structure(list(ID = c("A", "A", "A", "A", "B", "B", "B"), Counter = c(1L,
0L, 1L, 1L, 1L, 0L, 1L)), class = "data.frame", row.names = c(NA, -7L))
An alternative approach could be
df %>% group_by(ID) %>%
mutate(cs = accumulate(Counter, ~ifelse(.y == 0, .y, .x + .y)))
Checking it on data provided by dear @Ronak, in his comments
df <- structure(list(ID = c("A", "A", "A", "A", "A", "B", "B", "B"), Counter = c(1L, 0L, 1L, 1L, 1L, 1L, 0L, 1L)), class = "data.frame", row.names = c(NA, -8L))
df %>% group_by(ID) %>%
mutate(cs = accumulate(Counter, ~ifelse(.y == 0, .y, .x + .y)))
# A tibble: 8 x 3
# Groups: ID [2]
ID Counter cs
<chr> <int> <int>
1 A 1 1
2 A 0 0
3 A 1 1
4 A 1 2
5 A 1 3
6 B 1 1
7 B 0 0
8 B 1 1
