Conditional mutate statement based on ranked order in R using dplyr::mutate() and ifelse()
I am trying to define the start of an interval based on the known end_time of that interval in R using dplyr::mutate() with an ifelse() statement.
I can define the start_time for the first interval easily using minimum value time value but am getting stuck with the other start times. I've tried ranking them using dense_rank(), but I do not know the proper syntax to extract the end_time for the previous ranked value. The start_time for ranked > 1 should equal the end_time + 1 for the previous ranked value.
library(dplyr)
blks <- data.frame(Group = c(rep("A", 3), rep("B", 4)),
end_time = c(4, 8, 20, 5, 11, 15, 20))
expand.grid(time = 0:20,
Group = c("A","B")) %>%
left_join(mutate(blks, time = end_time), by = c("Group", "time")) %>%
group_by(Group) %>%
mutate(ranked = dense_rank(end_time),
start_time = ifelse(ranked == 1, min(time), "WHERE I NEED HELP"))
# else = the end_time from the previous ranked + 1
# end_time[ranked == ranked-1] + 1))
Desired result is:
mutate(blks, start_time = c(0, 5, 9, 0, 6, 12, 16))
r dplyr mutate
asked Dec 31 '18 at 18:39
sullijsullij
965
add a comment |
I am trying to define the start of an interval based on the known end_time of that interval in R using dplyr::mutate() with an ifelse() statement.
I can define the start_time for the first interval easily using minimum value time value but am getting stuck with the other start times. I've tried ranking them using dense_rank(), but I do not know the proper syntax to extract the end_time for the previous ranked value. The start_time for ranked > 1 should equal the end_time + 1 for the previous ranked value.
library(dplyr)
blks <- data.frame(Group = c(rep("A", 3), rep("B", 4)),
end_time = c(4, 8, 20, 5, 11, 15, 20))
expand.grid(time = 0:20,
Group = c("A","B")) %>%
left_join(mutate(blks, time = end_time), by = c("Group", "time")) %>%
group_by(Group) %>%
mutate(ranked = dense_rank(end_time),
start_time = ifelse(ranked == 1, min(time), "WHERE I NEED HELP"))
# else = the end_time from the previous ranked + 1
# end_time[ranked == ranked-1] + 1))
Desired result is:
mutate(blks, start_time = c(0, 5, 9, 0, 6, 12, 16))
r dplyr mutate
asked Dec 31 '18 at 18:39
sullijsullij
965
1
blks %>% group_by(Group) %>% mutate(start_time = c(0, head(end_time, -1) + 1))
– Henrik
Dec 31 '18 at 19:16
add a comment |
I am trying to define the start of an interval based on the known end_time of that interval in R using dplyr::mutate() with an ifelse() statement.
I can define the start_time for the first interval easily using minimum value time value but am getting stuck with the other start times. I've tried ranking them using dense_rank(), but I do not know the proper syntax to extract the end_time for the previous ranked value. The start_time for ranked > 1 should equal the end_time + 1 for the previous ranked value.
library(dplyr)
blks <- data.frame(Group = c(rep("A", 3), rep("B", 4)),
end_time = c(4, 8, 20, 5, 11, 15, 20))
expand.grid(time = 0:20,
Group = c("A","B")) %>%
left_join(mutate(blks, time = end_time), by = c("Group", "time")) %>%
group_by(Group) %>%
mutate(ranked = dense_rank(end_time),
start_time = ifelse(ranked == 1, min(time), "WHERE I NEED HELP"))
# else = the end_time from the previous ranked + 1
# end_time[ranked == ranked-1] + 1))
Desired result is:
mutate(blks, start_time = c(0, 5, 9, 0, 6, 12, 16))
r dplyr mutate
asked Dec 31 '18 at 18:39
sullijsullij
965
I am trying to define the start of an interval based on the known end_time of that interval in R using dplyr::mutate() with an ifelse() statement.
I can define the start_time for the first interval easily using minimum value time value but am getting stuck with the other start times. I've tried ranking them using dense_rank(), but I do not know the proper syntax to extract the end_time for the previous ranked value. The start_time for ranked > 1 should equal the end_time + 1 for the previous ranked value.
library(dplyr)
blks <- data.frame(Group = c(rep("A", 3), rep("B", 4)),
end_time = c(4, 8, 20, 5, 11, 15, 20))
expand.grid(time = 0:20,
Group = c("A","B")) %>%
left_join(mutate(blks, time = end_time), by = c("Group", "time")) %>%
group_by(Group) %>%
mutate(ranked = dense_rank(end_time),
start_time = ifelse(ranked == 1, min(time), "WHERE I NEED HELP"))
# else = the end_time from the previous ranked + 1
# end_time[ranked == ranked-1] + 1))
Desired result is:
mutate(blks, start_time = c(0, 5, 9, 0, 6, 12, 16))
r dplyr mutate
r dplyr mutate
asked Dec 31 '18 at 18:39
sullijsullij
965
asked Dec 31 '18 at 18:39
sullijsullij
965
asked Dec 31 '18 at 18:39
sullijsullij
965
asked Dec 31 '18 at 18:39
sullijsullij
965
asked Dec 31 '18 at 18:39
sullijsullij
965
965
1
blks %>% group_by(Group) %>% mutate(start_time = c(0, head(end_time, -1) + 1))
– Henrik
Dec 31 '18 at 19:16
add a comment |
1
blks %>% group_by(Group) %>% mutate(start_time = c(0, head(end_time, -1) + 1))
– Henrik
Dec 31 '18 at 19:16
1
1
blks %>% group_by(Group) %>% mutate(start_time = c(0, head(end_time, -1) + 1)) – Henrik
Dec 31 '18 at 19:16
blks %>% group_by(Group) %>% mutate(start_time = c(0, head(end_time, -1) + 1)) – Henrik
Dec 31 '18 at 19:16
add a comment |
1 Answer
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votes
We can try dplyr::lag with deafult=-1 then add 1
library(dplyr)
blks %>% group_by(Group) %>% mutate(start_time = lag(end_time,default=-1)+1)
# A tibble: 7 x 3
# Groups: Group [2]
Group end_time start_time
< fct> <dbl> <dbl>
1 A 4 0
2 A 8 5
3 A 20 9
4 B 5 0
5 B 11 6
6 B 15 12
7 B 20 16
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
add a comment |
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1 Answer
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active
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1 Answer
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active
oldest
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oldest
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active
oldest
votes
We can try dplyr::lag with deafult=-1 then add 1
library(dplyr)
blks %>% group_by(Group) %>% mutate(start_time = lag(end_time,default=-1)+1)
# A tibble: 7 x 3
# Groups: Group [2]
Group end_time start_time
< fct> <dbl> <dbl>
1 A 4 0
2 A 8 5
3 A 20 9
4 B 5 0
5 B 11 6
6 B 15 12
7 B 20 16
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
add a comment |
We can try dplyr::lag with deafult=-1 then add 1
library(dplyr)
blks %>% group_by(Group) %>% mutate(start_time = lag(end_time,default=-1)+1)
# A tibble: 7 x 3
# Groups: Group [2]
Group end_time start_time
< fct> <dbl> <dbl>
1 A 4 0
2 A 8 5
3 A 20 9
4 B 5 0
5 B 11 6
6 B 15 12
7 B 20 16
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
add a comment |
We can try dplyr::lag with deafult=-1 then add 1
library(dplyr)
blks %>% group_by(Group) %>% mutate(start_time = lag(end_time,default=-1)+1)
# A tibble: 7 x 3
# Groups: Group [2]
Group end_time start_time
< fct> <dbl> <dbl>
1 A 4 0
2 A 8 5
3 A 20 9
4 B 5 0
5 B 11 6
6 B 15 12
7 B 20 16
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
We can try dplyr::lag with deafult=-1 then add 1
library(dplyr)
blks %>% group_by(Group) %>% mutate(start_time = lag(end_time,default=-1)+1)
# A tibble: 7 x 3
# Groups: Group [2]
Group end_time start_time
< fct> <dbl> <dbl>
1 A 4 0
2 A 8 5
3 A 20 9
4 B 5 0
5 B 11 6
6 B 15 12
7 B 20 16
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
answered Jan 1 at 23:22
A. SulimanA. Suliman
5,13541122
5,13541122
add a comment |
add a comment |
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blks %>% group_by(Group) %>% mutate(start_time = c(0, head(end_time, -1) + 1))– Henrik
Dec 31 '18 at 19:16