Make new colum based on values in two different columns by group

I want make a ‘new column’ with values from ‘number’ only for ‘sp.name’ (grouping variable) where both responses ‘young’ and ‘adult’ are present; if not, enter 0 in the ‘new column’.

df <- data.frame(sp.name= c('a','a', 'b', 'b' ,'c', 'd' ),
                 number=c(2,2,3, 3,4,4),
                 stage= c('adult', 'young', 'young','adult', 'adult', 'young'))

Here is what I tried.

df %>%
  group_by(sp.name) %>%
  mutate(new_column = ifelse('young' %in% stage & 'adult' %in% stage, 
                                             number[stage == 'adult'], 0))

But my code reproduces value for ‘young’ also to the new column, I want only values related to ‘adult’.

Desired output:

>Solution :

df %>% 
  group_by(sp.name) %>% 
  mutate(new = (any(stage == 'adult') & any(stage == 'young') & stage == 'adult') * number)

#> # A tibble: 6 x 4
#> # Groups:   sp.name [4]
#>   sp.name number stage   new
#>   <chr>    <dbl> <chr> <dbl>
#> 1 a            2 adult     2
#> 2 a            2 young     0
#> 3 b            3 young     0
#> 4 b            3 adult     3
#> 5 c            4 adult     0
#> 6 d            4 young     0