remove NA values and combine non NA values into a single column - r

Question

I have a data set which has numeric and NA values in all columns. I would like to create a new column with all non NA values and preserve the row names
v1 v2 v3 v4 v5
a 1 NA NA NA NA
b NA 2 NA NA NA
c NA NA 3 NA NA
d NA NA NA 4 NA
e NA NA NA NA 5
I have tried using the coalesce function from dplyr
digital_metrics_FB <- fb_all_data %>%
mutate(fb_metrics = coalesce("v1",
"v2",
"v3",
"v4",
"v5"))
and also tried an apply function
df2 <- sapply(fb_all_data,function(x) x[!is.na(x)])
still cannot get it to work.
I am looking for the final result to be where all non NA values come together in the final column and the row names are preserved
final
a 1
b 2
c 3
d 4
e 5
any help would be much appreciated

Answer 1

We can use pmax
do.call(pmax, c(fb_all_data , na.rm = TRUE))
If there are more than one non-NA element and want to combine as a string, a simple base R option would be
data.frame(final = apply(fb_all_data, 1, function(x) toString(x[!is.na(x)])))
Or using coalesce
library(dplyr)
library(tibble)
fb_all_data %>%
rownames_to_column('rn') %>%
transmute(rn, final = coalesce(v1, v2, v3, v4, v5)) %>%
column_to_rownames('rn')
# final
#a 1
#b 2
#c 3
#d 4
#e 5
Or using tidyverse, for multiple non-NA elements
fb_all_data %>%
rownames_to_column('rn') %>%
transmute(rn, final = pmap_chr(.[-1], ~ c(...) %>%
na.omit %>%
toString)) %>%
column_to_rownames('rn')
NOTE: Here we are showing data that the OP showed as example and not some other dataset
data
fb_all_data <- structure(list(v1 = c(1L, NA, NA, NA, NA), v2 = c(NA, 2L, NA,
NA, NA), v3 = c(NA, NA, 3L, NA, NA), v4 = c(NA, NA, NA, 4L, NA
), v5 = c(NA, NA, NA, NA, 5L)), class = "data.frame",
row.names = c("a",
"b", "c", "d", "e"))

Answer 2

With tidyverse, you can do:
df %>%
rownames_to_column() %>%
gather(var, val, -1, na.rm = TRUE) %>%
group_by(rowname) %>%
summarise(val = paste(val, collapse = ", "))
rowname val
<chr> <chr>
1 a 1
2 b 2, 3
3 c 3
4 d 4
5 e 5
Sample data to have a row with more than one non-NA value:
df <- read.table(text = " v1 v2 v3 v4 v5
a 1 NA NA NA NA
b NA 2 3 NA NA
c NA NA 3 NA NA
d NA NA NA 4 NA
e NA NA NA NA 5", header = TRUE)