Fill row values to the right of some value
1
Given the following data frame, I need to be able to fill out values in each row to the right until the next value is encountered in which case I need to fill that value out etc. until I reach the end of the row.
# load data
id <- LETTERS[1:7]
X2000 <- c(NA,NA,NA,NA,100,NA,NA)
X2001 <- c(NA,200,80,NA,205,50,NA)
X2002 <- c(NA,300,NA,300,NA,NA,NA)
X2003 <- c(400,NA,70,NA,NA,NA,600)
X2004 <- c(NA,500,NA,NA,NA,NA,NA)
dat <- data.frame(id,X2000,X2001,X2002,X2003,X2004)
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 NA
B NA 200 300 NA 500
C NA 80 NA 70 NA
D NA NA 300 NA NA
E 100 205 NA NA NA
F NA 50 NA NA NA
G NA NA NA 600 NA
The resulting dataframe should look like this:
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 400
B NA 200 300 300 500
C NA 80 80 70 70
D NA NA 300 300 300
E 100 205 205 205 205
F NA 50 50 50 50
G NA NA NA 600 600
Any clever way of doing this? Thanks.
r
asked Nov 20 at 22:46
user1658170
1691617
add a comment |
1
Given the following data frame, I need to be able to fill out values in each row to the right until the next value is encountered in which case I need to fill that value out etc. until I reach the end of the row.
# load data
id <- LETTERS[1:7]
X2000 <- c(NA,NA,NA,NA,100,NA,NA)
X2001 <- c(NA,200,80,NA,205,50,NA)
X2002 <- c(NA,300,NA,300,NA,NA,NA)
X2003 <- c(400,NA,70,NA,NA,NA,600)
X2004 <- c(NA,500,NA,NA,NA,NA,NA)
dat <- data.frame(id,X2000,X2001,X2002,X2003,X2004)
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 NA
B NA 200 300 NA 500
C NA 80 NA 70 NA
D NA NA 300 NA NA
E 100 205 NA NA NA
F NA 50 NA NA NA
G NA NA NA 600 NA
The resulting dataframe should look like this:
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 400
B NA 200 300 300 500
C NA 80 80 70 70
D NA NA 300 300 300
E 100 205 205 205 205
F NA 50 50 50 50
G NA NA NA 600 600
Any clever way of doing this? Thanks.
r
asked Nov 20 at 22:46
user1658170
1691617
Related posts.cbind(dat[1], t(zoo::na.locf(t(dat[-1]))))
– Henrik
Nov 20 at 23:09
add a comment |
1
1
1
Given the following data frame, I need to be able to fill out values in each row to the right until the next value is encountered in which case I need to fill that value out etc. until I reach the end of the row.
# load data
id <- LETTERS[1:7]
X2000 <- c(NA,NA,NA,NA,100,NA,NA)
X2001 <- c(NA,200,80,NA,205,50,NA)
X2002 <- c(NA,300,NA,300,NA,NA,NA)
X2003 <- c(400,NA,70,NA,NA,NA,600)
X2004 <- c(NA,500,NA,NA,NA,NA,NA)
dat <- data.frame(id,X2000,X2001,X2002,X2003,X2004)
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 NA
B NA 200 300 NA 500
C NA 80 NA 70 NA
D NA NA 300 NA NA
E 100 205 NA NA NA
F NA 50 NA NA NA
G NA NA NA 600 NA
The resulting dataframe should look like this:
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 400
B NA 200 300 300 500
C NA 80 80 70 70
D NA NA 300 300 300
E 100 205 205 205 205
F NA 50 50 50 50
G NA NA NA 600 600
Any clever way of doing this? Thanks.
r
asked Nov 20 at 22:46
user1658170
1691617
Given the following data frame, I need to be able to fill out values in each row to the right until the next value is encountered in which case I need to fill that value out etc. until I reach the end of the row.
# load data
id <- LETTERS[1:7]
X2000 <- c(NA,NA,NA,NA,100,NA,NA)
X2001 <- c(NA,200,80,NA,205,50,NA)
X2002 <- c(NA,300,NA,300,NA,NA,NA)
X2003 <- c(400,NA,70,NA,NA,NA,600)
X2004 <- c(NA,500,NA,NA,NA,NA,NA)
dat <- data.frame(id,X2000,X2001,X2002,X2003,X2004)
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 NA
B NA 200 300 NA 500
C NA 80 NA 70 NA
D NA NA 300 NA NA
E 100 205 NA NA NA
F NA 50 NA NA NA
G NA NA NA 600 NA
The resulting dataframe should look like this:
id X2000 X2001 X2002 X2003 X2004
A NA NA NA 400 400
B NA 200 300 300 500
C NA 80 80 70 70
D NA NA 300 300 300
E 100 205 205 205 205
F NA 50 50 50 50
G NA NA NA 600 600
Any clever way of doing this? Thanks.
r
r
asked Nov 20 at 22:46
user1658170
1691617
asked Nov 20 at 22:46
user1658170
1691617
asked Nov 20 at 22:46
user1658170
1691617
asked Nov 20 at 22:46
user1658170
1691617
asked Nov 20 at 22:46
user1658170
1691617
1691617
Related posts.cbind(dat[1], t(zoo::na.locf(t(dat[-1]))))
– Henrik
Nov 20 at 23:09
add a comment |
Related posts.cbind(dat[1], t(zoo::na.locf(t(dat[-1]))))
– Henrik
Nov 20 at 23:09
Related posts.
cbind(dat[1], t(zoo::na.locf(t(dat[-1]))))– Henrik
Nov 20 at 23:09
Related posts.
cbind(dat[1], t(zoo::na.locf(t(dat[-1]))))– Henrik
Nov 20 at 23:09
add a comment |
2 Answers
2
active
oldest
votes
1
Here's one way with dplyr and tidyr -
dat %>%
gather(year, value, -id) %>%
group_by(id) %>%
arrange(id, year) %>%
fill(value, .direction = "down") %>%
ungroup() %>%
spread(year, value)
# A tibble: 7 x 6
id X2000 X2001 X2002 X2003 X2004
<fct> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A NA NA NA 400 400
2 B NA 200 300 300 500
3 C NA 80.0 80.0 70.0 70.0
4 D NA NA 300 300 300
5 E 100 205 205 205 205
6 F NA 50.0 50.0 50.0 50.0
7 G NA NA NA 600 600
answered Nov 20 at 23:01
Shree
3,2861323
This was perfect
– user1658170
Nov 22 at 18:42
add a comment |
1
We could apply with na.locf
library(zoo)
dat[-1] <- t(apply(dat[-1], 1, na.locf, na.rm = FALSE))
dat
# id X2000 X2001 X2002 X2003 X2004
#1 A NA NA NA 400 400
#2 B NA 200 300 300 500
#3 C NA 80 80 70 70
#4 D NA NA 300 300 300
#5 E 100 205 205 205 205
#6 F NA 50 50 50 50
#7 G NA NA NA 600 600
answered Nov 21 at 5:06
akrun
396k13187260
1
Note that we can usena.locf0which defaults tona.rm=FALSE.
– G. Grothendieck
Nov 22 at 13:50
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
1
Here's one way with dplyr and tidyr -
dat %>%
gather(year, value, -id) %>%
group_by(id) %>%
arrange(id, year) %>%
fill(value, .direction = "down") %>%
ungroup() %>%
spread(year, value)
# A tibble: 7 x 6
id X2000 X2001 X2002 X2003 X2004
<fct> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A NA NA NA 400 400
2 B NA 200 300 300 500
3 C NA 80.0 80.0 70.0 70.0
4 D NA NA 300 300 300
5 E 100 205 205 205 205
6 F NA 50.0 50.0 50.0 50.0
7 G NA NA NA 600 600
answered Nov 20 at 23:01
Shree
3,2861323
This was perfect
– user1658170
Nov 22 at 18:42
add a comment |
1
Here's one way with dplyr and tidyr -
dat %>%
gather(year, value, -id) %>%
group_by(id) %>%
arrange(id, year) %>%
fill(value, .direction = "down") %>%
ungroup() %>%
spread(year, value)
# A tibble: 7 x 6
id X2000 X2001 X2002 X2003 X2004
<fct> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A NA NA NA 400 400
2 B NA 200 300 300 500
3 C NA 80.0 80.0 70.0 70.0
4 D NA NA 300 300 300
5 E 100 205 205 205 205
6 F NA 50.0 50.0 50.0 50.0
7 G NA NA NA 600 600
answered Nov 20 at 23:01
Shree
3,2861323
This was perfect
– user1658170
Nov 22 at 18:42
add a comment |
1
1
1
Here's one way with dplyr and tidyr -
dat %>%
gather(year, value, -id) %>%
group_by(id) %>%
arrange(id, year) %>%
fill(value, .direction = "down") %>%
ungroup() %>%
spread(year, value)
# A tibble: 7 x 6
id X2000 X2001 X2002 X2003 X2004
<fct> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A NA NA NA 400 400
2 B NA 200 300 300 500
3 C NA 80.0 80.0 70.0 70.0
4 D NA NA 300 300 300
5 E 100 205 205 205 205
6 F NA 50.0 50.0 50.0 50.0
7 G NA NA NA 600 600
answered Nov 20 at 23:01
Shree
3,2861323
Here's one way with dplyr and tidyr -
dat %>%
gather(year, value, -id) %>%
group_by(id) %>%
arrange(id, year) %>%
fill(value, .direction = "down") %>%
ungroup() %>%
spread(year, value)
# A tibble: 7 x 6
id X2000 X2001 X2002 X2003 X2004
<fct> <dbl> <dbl> <dbl> <dbl> <dbl>
1 A NA NA NA 400 400
2 B NA 200 300 300 500
3 C NA 80.0 80.0 70.0 70.0
4 D NA NA 300 300 300
5 E 100 205 205 205 205
6 F NA 50.0 50.0 50.0 50.0
7 G NA NA NA 600 600
answered Nov 20 at 23:01
Shree
3,2861323
answered Nov 20 at 23:01
Shree
3,2861323
answered Nov 20 at 23:01
Shree
3,2861323
answered Nov 20 at 23:01
Shree
3,2861323
3,2861323
This was perfect
– user1658170
Nov 22 at 18:42
add a comment |
This was perfect
– user1658170
Nov 22 at 18:42
This was perfect
– user1658170
Nov 22 at 18:42
This was perfect
– user1658170
Nov 22 at 18:42
add a comment |
1
We could apply with na.locf
library(zoo)
dat[-1] <- t(apply(dat[-1], 1, na.locf, na.rm = FALSE))
dat
# id X2000 X2001 X2002 X2003 X2004
#1 A NA NA NA 400 400
#2 B NA 200 300 300 500
#3 C NA 80 80 70 70
#4 D NA NA 300 300 300
#5 E 100 205 205 205 205
#6 F NA 50 50 50 50
#7 G NA NA NA 600 600
answered Nov 21 at 5:06
akrun
396k13187260
1
Note that we can usena.locf0which defaults tona.rm=FALSE.
– G. Grothendieck
Nov 22 at 13:50
add a comment |
1
We could apply with na.locf
library(zoo)
dat[-1] <- t(apply(dat[-1], 1, na.locf, na.rm = FALSE))
dat
# id X2000 X2001 X2002 X2003 X2004
#1 A NA NA NA 400 400
#2 B NA 200 300 300 500
#3 C NA 80 80 70 70
#4 D NA NA 300 300 300
#5 E 100 205 205 205 205
#6 F NA 50 50 50 50
#7 G NA NA NA 600 600
answered Nov 21 at 5:06
akrun
396k13187260
1
Note that we can usena.locf0which defaults tona.rm=FALSE.
– G. Grothendieck
Nov 22 at 13:50
add a comment |
1
1
1
We could apply with na.locf
library(zoo)
dat[-1] <- t(apply(dat[-1], 1, na.locf, na.rm = FALSE))
dat
# id X2000 X2001 X2002 X2003 X2004
#1 A NA NA NA 400 400
#2 B NA 200 300 300 500
#3 C NA 80 80 70 70
#4 D NA NA 300 300 300
#5 E 100 205 205 205 205
#6 F NA 50 50 50 50
#7 G NA NA NA 600 600
answered Nov 21 at 5:06
akrun
396k13187260
We could apply with na.locf
library(zoo)
dat[-1] <- t(apply(dat[-1], 1, na.locf, na.rm = FALSE))
dat
# id X2000 X2001 X2002 X2003 X2004
#1 A NA NA NA 400 400
#2 B NA 200 300 300 500
#3 C NA 80 80 70 70
#4 D NA NA 300 300 300
#5 E 100 205 205 205 205
#6 F NA 50 50 50 50
#7 G NA NA NA 600 600
answered Nov 21 at 5:06
akrun
396k13187260
answered Nov 21 at 5:06
akrun
396k13187260
answered Nov 21 at 5:06
akrun
396k13187260
answered Nov 21 at 5:06
akrun
396k13187260
396k13187260
1
Note that we can usena.locf0which defaults tona.rm=FALSE.
– G. Grothendieck
Nov 22 at 13:50
add a comment |
1
Note that we can usena.locf0which defaults tona.rm=FALSE.
– G. Grothendieck
Nov 22 at 13:50
1
1
Note that we can use
na.locf0 which defaults to na.rm=FALSE .– G. Grothendieck
Nov 22 at 13:50
Note that we can use
na.locf0 which defaults to na.rm=FALSE .– G. Grothendieck
Nov 22 at 13:50
add a comment |
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Related posts.
cbind(dat[1], t(zoo::na.locf(t(dat[-1]))))– Henrik
Nov 20 at 23:09