Omitting NAs just won't work

[anyway01]

Hello everybody!

Currently I am trying to generate a new sum variable with mutate(). I want to generate the sums of 10 different variables where row-wise are always different numbers of figures to sum up. So in one row only 2 of 10 variables have summable numbers (The rest is NA), in other rows there 4 or 6, for example.
I already know that in this kind of data frame it's important to omit NAs to sum up rows. That's why I wanted to use na.rm=TRUE, but in mutate() it's just gonna generate a column named "na.rm" with all rows showing the content "TRUE".

Now I have already tried the following approaches:

library(dplyr)
data %>% 
  rowwise() %>% 
  mutate(sum = sum(a,b,c, na.rm=TRUE))

data %>%
  mutate(sum = rowSums(., na.rm = TRUE))

Source: r - ignore NA in dplyr row sum - Stack Overflow

None of these approaches works in my case. The sum variable just remains NA in all rows which contain at least one NA. So I guess the NAs won't be omitted properly for some reason, even though I put na.rm on "TRUE".
I have also seen that the operations in the code blocks above just won't do anything. They won't generate a new sum column or change the existing one from the mutate() operation which won't omit the NAs.

I gotta overlook something and I just don't know what.

[siddharthprabhu]

The rowSums() approach works fine if you nest the selection inside it.

library(dplyr, warn.conflicts = FALSE)

data <- tibble(a = c(4, NA, 5),
               b = c(NA, NA, 3),
               c = c(9, 2, 4))

data %>% 
  mutate(sum = rowSums(select(., a, b, c), na.rm = TRUE))
#> # A tibble: 3 x 4
#>       a     b     c   sum
#>   <dbl> <dbl> <dbl> <dbl>
#> 1     4    NA     9    13
#> 2    NA    NA     2     2
#> 3     5     3     4    12

^{Created on 2020-09-14 by the reprex package (v0.3.0)}

[anyway01]

Now it's getting really weird, siddharthprabhu:

I have copy-pasted your code (which works just fine here) in my code Markdown and it just won't generate a sum column.

What you can see here is the result after I executed the copy-pasted operations. Is there something which blocks this operation...?

[siddharthprabhu]

You haven't assigned the result back to data. So View(data) just gives you the original tibble.

[anyway01]

Dear siddharthprabhu,

It just worked out fine. I am just as thankful to you as I am feeling stupid right now.

Best regards

[siddharthprabhu]

No worries. It happens to the best of us at times.