# Tricky behavior with grouped summarize sum for groups with only NAs

Hi,

I know that `sum(NA, na.rm = TRUE)` results in 0. However, I wouldn't necessarily want this 0 to appear in a summarise() output. Please see the minimal example below.

``````tbl <- tibble(id = c(1,2), values = c(NA, 5))

tbl %>% group_by(id) %>% summarise(tot = sum(values, na.rm = TRUE))
#> # A tibble: 2 × 2
#>      id   tot
#>   <dbl> <dbl>
#> 1     1     0
#> 2     2     5
``````

Subsequent calculations using the `tot` column would be wrong (e.g., mean of `tot`). I know this is a symptom of the `sum()` function, but was wondering if there is a "safer" way of doing such summarize? I suppose one approach is an initial test, e.g.,

``````tbl %>% group_by(id) %>% summarise(tot = if_else(all(is.na(values)), NA, sum(values, na.rm = TRUE)))
``````

Are there better ways to avoid this potential pitfall? Thank you in advance for any feedback and guidance.

The mean function has an na.rm option as well.

``````> tbl <- tibble(id = c(1,2), values = c(NA, 5))
>
> tbl %>%
>   group_by(id) %>% summarise(
>     tot_sum = sum(values, na.rm = TRUE),
>     tot_mean = mean(values, na.rm = TRUE)
>   )

# A tibble: 2 x 3
id tot_sum tot_mean
<dbl>   <dbl>    <dbl>
1     1       0      NaN
2     2       5        5
``````

for accurate downstream calculations, simple use the NA , as there purpose of existence is to work in the way you would require.

Displaying nicely formatted results for users should happen downstream of your calculations; you can decide on appropriate way to print the NA info depending on that.

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