Let's say I have the following data:

```
values = data.frame(score = c(1, 2, 3, 4, 5, 999, 2, 3, 999, 4),
                    score_2 = c(1, 4, 8 , 4, 999, 2, 3, 2, 1, 0))
values %>% 
  summarize(mean_score = mean(score),
            mean_score_2 = mean(score_2))

```

I want to compute the mean of each of the columns in the dataset while ignoring the value "999." 

So I can do something like this: 

```
values %>% 
  filter_all(all_vars(!grepl('999',.))) %>%
  summarize(mean_score = mean(score),
            mean_score_2 = mean(score_2))

```

But this will remove rows 6, 9, and 5 from both score and score\_2 (because that's the location of 999). How do I selectively compute the means while ignoring certain values without eliminating entire rows? 

For `score` the resulting output should be `3`, for `score_2` the resulting output should be `2.78`