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r - dplyr::first() to choose first non NA value

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?

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1 Answer

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by (71.8m points)

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

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