Adding a new column with mutate and group by
0
I want to create a new column called age based on a previous column and group by functions. The dataset is as follows:
tid<- c(1,2,3,4, 1,2,3,4,1,2,3,4)
active<- c(0,1,0,4, 0,0,0,1,0,0,1,0)
person<- c('John', 'John','John', 'John', 'Emma', 'Emma','Emma','Emma', 'Edward', 'Edward', 'Edward', 'Edward')
df<- data.frame(tid, active, person)
I want to create age which starts with 0 when the person is first active i.e., the value of active becomes greater than 0 for first time and then incrementally gets added with one value for the next record. Any suggestions?
I am expecting the output as follows:
name age
John 0
John 0
John 1
John 2
Emma 0
Emma 0
Emma 0
Emma 0
Edward 0
Edward 0
Edward 0
Edward 1
r dplyr plyr tidyr
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
add a comment |
0
I want to create a new column called age based on a previous column and group by functions. The dataset is as follows:
tid<- c(1,2,3,4, 1,2,3,4,1,2,3,4)
active<- c(0,1,0,4, 0,0,0,1,0,0,1,0)
person<- c('John', 'John','John', 'John', 'Emma', 'Emma','Emma','Emma', 'Edward', 'Edward', 'Edward', 'Edward')
df<- data.frame(tid, active, person)
I want to create age which starts with 0 when the person is first active i.e., the value of active becomes greater than 0 for first time and then incrementally gets added with one value for the next record. Any suggestions?
I am expecting the output as follows:
name age
John 0
John 0
John 1
John 2
Emma 0
Emma 0
Emma 0
Emma 0
Edward 0
Edward 0
Edward 0
Edward 1
r dplyr plyr tidyr
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
What have you tried? Please give us an example of some strategies / code you have attempted
– sorearm
Nov 19 '18 at 11:07
Shouldn't John be 0,0,1,1?
– snoram
Nov 19 '18 at 11:15
no it is supposed to be 0,0,1,2 as the age of him will be incremented to the next value in the later period i.e. in tid 1 he is 0 , 2 he is still 0, as he became active and in 3 he gets 1 and 4 he gets 2
– user3570187
Nov 19 '18 at 11:19
add a comment |
0
0
0
I want to create a new column called age based on a previous column and group by functions. The dataset is as follows:
tid<- c(1,2,3,4, 1,2,3,4,1,2,3,4)
active<- c(0,1,0,4, 0,0,0,1,0,0,1,0)
person<- c('John', 'John','John', 'John', 'Emma', 'Emma','Emma','Emma', 'Edward', 'Edward', 'Edward', 'Edward')
df<- data.frame(tid, active, person)
I want to create age which starts with 0 when the person is first active i.e., the value of active becomes greater than 0 for first time and then incrementally gets added with one value for the next record. Any suggestions?
I am expecting the output as follows:
name age
John 0
John 0
John 1
John 2
Emma 0
Emma 0
Emma 0
Emma 0
Edward 0
Edward 0
Edward 0
Edward 1
r dplyr plyr tidyr
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
I want to create a new column called age based on a previous column and group by functions. The dataset is as follows:
tid<- c(1,2,3,4, 1,2,3,4,1,2,3,4)
active<- c(0,1,0,4, 0,0,0,1,0,0,1,0)
person<- c('John', 'John','John', 'John', 'Emma', 'Emma','Emma','Emma', 'Edward', 'Edward', 'Edward', 'Edward')
df<- data.frame(tid, active, person)
I want to create age which starts with 0 when the person is first active i.e., the value of active becomes greater than 0 for first time and then incrementally gets added with one value for the next record. Any suggestions?
I am expecting the output as follows:
name age
John 0
John 0
John 1
John 2
Emma 0
Emma 0
Emma 0
Emma 0
Edward 0
Edward 0
Edward 0
Edward 1
r dplyr plyr tidyr
r dplyr plyr tidyr
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
asked Nov 19 '18 at 11:05
user3570187user3570187
625621
625621
What have you tried? Please give us an example of some strategies / code you have attempted
– sorearm
Nov 19 '18 at 11:07
Shouldn't John be 0,0,1,1?
– snoram
Nov 19 '18 at 11:15
no it is supposed to be 0,0,1,2 as the age of him will be incremented to the next value in the later period i.e. in tid 1 he is 0 , 2 he is still 0, as he became active and in 3 he gets 1 and 4 he gets 2
– user3570187
Nov 19 '18 at 11:19
add a comment |
What have you tried? Please give us an example of some strategies / code you have attempted
– sorearm
Nov 19 '18 at 11:07
Shouldn't John be 0,0,1,1?
– snoram
Nov 19 '18 at 11:15
no it is supposed to be 0,0,1,2 as the age of him will be incremented to the next value in the later period i.e. in tid 1 he is 0 , 2 he is still 0, as he became active and in 3 he gets 1 and 4 he gets 2
– user3570187
Nov 19 '18 at 11:19
What have you tried? Please give us an example of some strategies / code you have attempted
– sorearm
Nov 19 '18 at 11:07
What have you tried? Please give us an example of some strategies / code you have attempted
– sorearm
Nov 19 '18 at 11:07
Shouldn't John be 0,0,1,1?
– snoram
Nov 19 '18 at 11:15
Shouldn't John be 0,0,1,1?
– snoram
Nov 19 '18 at 11:15
no it is supposed to be 0,0,1,2 as the age of him will be incremented to the next value in the later period i.e. in tid 1 he is 0 , 2 he is still 0, as he became active and in 3 he gets 1 and 4 he gets 2
– user3570187
Nov 19 '18 at 11:19
no it is supposed to be 0,0,1,2 as the age of him will be incremented to the next value in the later period i.e. in tid 1 he is 0 , 2 he is still 0, as he became active and in 3 he gets 1 and 4 he gets 2
– user3570187
Nov 19 '18 at 11:19
add a comment |
2 Answers
2
active
oldest
votes
2
Does this solve it for you?
library(dplyr)
df %>%
group_by(person) %>%
arrange(person, tid) %>%
mutate(active_dummy = if_else(lag(cumsum(active)) > 0, 1, 0, 0),
age = cumsum(active_dummy)) %>%
select(person, age)
which gives you
# A tibble: 12 x 2
# Groups: person [3]
person age
<chr> <dbl>
1 John 0.
2 John 0.
3 John 1.
4 John 2.
5 Emma 0.
6 Emma 0.
7 Emma 0.
8 Emma 0.
9 Edward 0.
10 Edward 0.
11 Edward 0.
12 Edward 1.
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
add a comment |
0
An alternative solution that also does the job:
library(tidyverse)
age_counter = df %>%
arrange(tid) %>%
group_by(person) %>%
filter(cumsum(active) > 0) %>%
mutate(age = row_number() - 1)
df %>%
left_join(age_counter) %>%
replace_na(list(age = 0)) %>%
select(person, age)
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
Does this solve it for you?
library(dplyr)
df %>%
group_by(person) %>%
arrange(person, tid) %>%
mutate(active_dummy = if_else(lag(cumsum(active)) > 0, 1, 0, 0),
age = cumsum(active_dummy)) %>%
select(person, age)
which gives you
# A tibble: 12 x 2
# Groups: person [3]
person age
<chr> <dbl>
1 John 0.
2 John 0.
3 John 1.
4 John 2.
5 Emma 0.
6 Emma 0.
7 Emma 0.
8 Emma 0.
9 Edward 0.
10 Edward 0.
11 Edward 0.
12 Edward 1.
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
add a comment |
2
Does this solve it for you?
library(dplyr)
df %>%
group_by(person) %>%
arrange(person, tid) %>%
mutate(active_dummy = if_else(lag(cumsum(active)) > 0, 1, 0, 0),
age = cumsum(active_dummy)) %>%
select(person, age)
which gives you
# A tibble: 12 x 2
# Groups: person [3]
person age
<chr> <dbl>
1 John 0.
2 John 0.
3 John 1.
4 John 2.
5 Emma 0.
6 Emma 0.
7 Emma 0.
8 Emma 0.
9 Edward 0.
10 Edward 0.
11 Edward 0.
12 Edward 1.
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
add a comment |
2
2
2
Does this solve it for you?
library(dplyr)
df %>%
group_by(person) %>%
arrange(person, tid) %>%
mutate(active_dummy = if_else(lag(cumsum(active)) > 0, 1, 0, 0),
age = cumsum(active_dummy)) %>%
select(person, age)
which gives you
# A tibble: 12 x 2
# Groups: person [3]
person age
<chr> <dbl>
1 John 0.
2 John 0.
3 John 1.
4 John 2.
5 Emma 0.
6 Emma 0.
7 Emma 0.
8 Emma 0.
9 Edward 0.
10 Edward 0.
11 Edward 0.
12 Edward 1.
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
Does this solve it for you?
library(dplyr)
df %>%
group_by(person) %>%
arrange(person, tid) %>%
mutate(active_dummy = if_else(lag(cumsum(active)) > 0, 1, 0, 0),
age = cumsum(active_dummy)) %>%
select(person, age)
which gives you
# A tibble: 12 x 2
# Groups: person [3]
person age
<chr> <dbl>
1 John 0.
2 John 0.
3 John 1.
4 John 2.
5 Emma 0.
6 Emma 0.
7 Emma 0.
8 Emma 0.
9 Edward 0.
10 Edward 0.
11 Edward 0.
12 Edward 1.
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
edited Nov 19 '18 at 12:01
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
answered Nov 19 '18 at 11:16
davsjobdavsjob
57236
57236
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
add a comment |
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
why do you have the >0,1,0,0 there? it is not generic enough, it should be 0 when the active sum =1 and then increments
– user3570187
Nov 19 '18 at 11:23
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
thanks, it worked, you need to add arrange(tid) to make it more generic enough
– user3570187
Nov 19 '18 at 11:57
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
@user3570187 You are right! I update the answer.
– davsjob
Nov 19 '18 at 11:59
add a comment |
0
An alternative solution that also does the job:
library(tidyverse)
age_counter = df %>%
arrange(tid) %>%
group_by(person) %>%
filter(cumsum(active) > 0) %>%
mutate(age = row_number() - 1)
df %>%
left_join(age_counter) %>%
replace_na(list(age = 0)) %>%
select(person, age)
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
add a comment |
0
An alternative solution that also does the job:
library(tidyverse)
age_counter = df %>%
arrange(tid) %>%
group_by(person) %>%
filter(cumsum(active) > 0) %>%
mutate(age = row_number() - 1)
df %>%
left_join(age_counter) %>%
replace_na(list(age = 0)) %>%
select(person, age)
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
add a comment |
0
0
0
An alternative solution that also does the job:
library(tidyverse)
age_counter = df %>%
arrange(tid) %>%
group_by(person) %>%
filter(cumsum(active) > 0) %>%
mutate(age = row_number() - 1)
df %>%
left_join(age_counter) %>%
replace_na(list(age = 0)) %>%
select(person, age)
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
An alternative solution that also does the job:
library(tidyverse)
age_counter = df %>%
arrange(tid) %>%
group_by(person) %>%
filter(cumsum(active) > 0) %>%
mutate(age = row_number() - 1)
df %>%
left_join(age_counter) %>%
replace_na(list(age = 0)) %>%
select(person, age)
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
answered Nov 19 '18 at 12:25
vectorsonvectorson
213
213
add a comment |
add a comment |
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What have you tried? Please give us an example of some strategies / code you have attempted
– sorearm
Nov 19 '18 at 11:07
Shouldn't John be 0,0,1,1?
– snoram
Nov 19 '18 at 11:15
no it is supposed to be 0,0,1,2 as the age of him will be incremented to the next value in the later period i.e. in tid 1 he is 0 , 2 he is still 0, as he became active and in 3 he gets 1 and 4 he gets 2
– user3570187
Nov 19 '18 at 11:19