I came across with How to find the last column with a value (for each row) in Rsame problem? , except that I have rows with no values ​​(the whole row of NA).The sample provided in the post described does not have a full row of NAs.

I would like to know how should I modify the following? I don't want to wash out those lines with all NAs because they are useful in later analysis.

df %>%
  rowwise %>%
  mutate(m = {tmp <- c_across(starts_with ('m'))
               tail(na.omit(tmp), 1)}) %>%
  ungroup

Thank you so much!

uj5u.com enthusiastic netizens replied:

If all elements in the row are empty, then the general solution is to create a condition to pass back NAthese lines font>

library(dplyr)
df %>%
  rowwise %>%
  mutate(m = {tmp <- c_across(starts_with ('m'))
               if(all(is.na( tmp))) NA_character_ else
                   tail(na.omit(tmp), 1)}) %>%
  ungroup

-output

# A tibble: 4 × 5
     id m_1 m_2 m_3 m 
  <dbl> <chr> <chr> <chr> <chr>
1 1 a e i i
2 2 b <NA> <NA> b
3 3 <NA> <NA> <NA> <NA>
4 4 d h l l

If the OP only wants to return the last non-NA element, we can also add an index[1] to extract, font>NAWhen no elementAuto passback

df %>%
  rowwise %>%
  mutate(m = {tmp <- c_across(starts_with ('m'))
               tail(na.omit(tmp), 1)[1]}) %>% 
  ungroup
# A tibble: 4 × 5
     id m_1 m_2 m_3 m 
  <dbl> <chr> <chr> <chr> <chr>
1 1 a e i i
2 2 b <NA> <NA> b
3 3 <NA> <NA> <NA> <NA>
4 4 d h l l

Data

df <- structure(list(id= c(1, 2, 3, 4), m_1 = c("a", "b", NA, "d"),
    m_2 = c("e", NA, NA, "h"), m_3 = c("i", NA, NA, "l")) span>, row.names = c(NA,
-4L), class = "data.frame")

uj5u.com enthusiastic netizens replied:

Using material from @akrun (thanks a lot) we can do this: font>

'\\b[^,] $' is a regular operation Format:

\\...means to escape (ie not match) this R is special in other languages, only A\

\\b...The metacharacter \b is an anchor ^ and $ notation.It matches at positions called "word boundaries".This match is zero-length.

[^,] ...represents the character class, here special ^caret: a character that is not,. here of "vertical-align: inherit;"> means one or more ,

library(dplyr)
library(tidyr)
library(stringr)

df %>%
  mutate(across(starts_with("m"), ~case_when(!is.na(.) ~ cur_column()),.names = 'new_{col}')) %>%
  unite(New_Col, starts_with('new'), na.rm = TRUE, sep = ', ') %>%
  mutate(New_Col = str_extract(New_Col, '\\b[^,] $'))

 id m_1 m_2 m_3 New_Col
1 1 a e i m_3
2 2 b <NA> <NA> m_1
3 3 <NA> <NA> <NA> <NA>
4 4 d h l m_3

library(tidyverse)
df <- data.frame(id = c( 1, 2, 3, 4), m_1 = c("a" , NA, "c", " d"), m_2 = c( "e", NA, "g", "h"), m_3 = c( "i", NA, NA, "l"))


df %>%
  rowwise() %>%
  mutate(
    nms = list(str_subset(names( df), "^m")),
    m = c_across(starts_with("m")) %>%
      {
        ifelse(test = all(is.na(.)),
          yes = NA,
          no = nms[which(.== tail(na.omit(.), 1))]
        )
      }
  ) %>%
  select(-nms)
#> # A tibble: 4 × 5
#> # Rowwise: 
#> id m_1 m_2 m_3 m 
#> <dbl> <chr> <chr> <chr> <chr>
#> 1 1 a e i m_3 
#> 2 2 <NA> <NA> <NA> <NA> 
#> 3 3 c g <NA> m_2 
#> 4 4 d h l m_3




# only the value no the column name
df %>%
  rowwise() %>%
  mutate(
    m = c_across(starts_with("m")) %>%
      {
        ifelse(test = all(is.na(.)),
          yes = NA,
          no = tail(na.omit(.), 1 )
        )
      }
  )
#> # A tibble: 4 × 5
#> # Rowwise: 
#> id m_1 m_2 m_3 m 
#> <dbl> <chr> <chr> <chr> <chr>
#> 1 1 a e i i 
#> 2 2 <NA> <NA> <NA> <NA> 
#> 3 3 c g <NA> g 
#> 4 4 d h l l