dplyr error: strange issue when combining group_by, mutate and ifelse. Is it a bug?

Question

I am having strange issues with dplyr and combination of group_by, mutate and ifelse. Consider the following data.frame

> df1
  crawl.id group.id hits.dif         


        

Answer 1

Wrap it all in as.numeric to force the output format so the NAs, which are logical by default, don't override the class of the output variable:

df1 %>%
  group_by(group.id) %>% 
  mutate( hits.consumed = as.numeric(ifelse(hits.diff<=0,-hits.diff,0)) )

#  crawl.id group.id hits.diff hits.consumed
#1        1        1        NA            NA
#2        1        2        NA            NA
#3        2        2         0             0
#4        1        3        NA            NA
#5        1        3        NA            NA
#6        1        3        NA            NA

Pretty sure this is the same issue as here: Custom sum function in dplyr returns inconsistent results , as this result suggests:

out <- df1[1:2,] %>%  mutate( hits.consumed = ifelse(hits.diff <= 0, -hits.diff, 0))
class(out$hits.consumed)
#[1] "logical"
out <- df1[1:3,] %>%  mutate( hits.consumed = ifelse(hits.diff <= 0, -hits.diff, 0))
class(out$hits.consumed)
#[1] "numeric"