I am looking for a way to extract the first and last non-NA value from each group. I am using dplyr::first() and dplyr::last(), but I can´t work out how to choose the first or last non-NA value.
library(dplyr)
set.seed(123)
d <- data.frame(
group = rep(1:3, each = 3),
year = rep(seq(2000,2002,1),3),
value = sample(1:9, r = T))
#Introduce NA values in first row of group 2 and last row of group 3
d %>%
mutate(
value = case_when(
group == 2 & year ==2000 ~ NA_integer_,
group == 3 & year ==2002 ~ NA_integer_,
TRUE ~ value))%>%
group_by(group) %>%
mutate(
first = dplyr::first(value),
last = dplyr::last(value))
RESULT (with issue)
# A tibble: 9 x 5
# Groups: group [3]
group year value first last
<int> <dbl> <int> <int> <int>
1 1 2000 3 3 4
2 1 2001 8 3 4
3 1 2002 4 3 4
4 2 2000 NA NA 1
5 2 2001 9 NA 1
6 2 2002 1 NA 1
7 3 2000 5 5 NA
8 3 2001 9 5 NA
9 3 2002 NA 5 NA
Can you help me make the values in the "first" column for group 2 = 9 and the values in the "last" column from group 3 = 9?
I very much prefer a tidyverse solution if one such exists?
Use na.omit, compare:
first(c(NA, 11, 22))
# [1] NA
first(na.omit(c(NA, 11, 22)))
# [1] 11
Using example data:
d %>%
mutate(
value = case_when(
group == 2 & year ==2000 ~ NA_integer_,
group == 3 & year ==2002 ~ NA_integer_,
TRUE ~ value))%>%
group_by(group) %>%
mutate(
first = dplyr::first(na.omit(value)),
last = dplyr::last(na.omit(value)))
# # A tibble: 9 x 5
# # Groups: group [3]
# group year value first last
# <int> <dbl> <int> <int> <int>
# 1 1 2000 3 3 4
# 2 1 2001 8 3 4
# 3 1 2002 4 3 4
# 4 2 2000 NA 9 1
# 5 2 2001 9 9 1
# 6 2 2002 1 9 1
# 7 3 2000 5 5 9
# 8 3 2001 9 5 9
# 9 3 2002 NA 5 9