I’m trying calculate the quintiles within each group of a dataframe. If I do:

```
mtcars %>%
group_by(gear,carb) %>%
summarise(total = sum(wt), .groups = "keep") %>%
mutate(rank = ntile(total,5))
```

all entries within the `rank`

column are equal to 1. What am I doing wrong here?

### >Solution :

Because when you `group_by(gear, carb)`

, unique combinations of these two variables are treated as a group. Since you used `summrise(..., .groups = "keep")`

, all grouping variables in the input are preserved. In this case, there’s only one unique combinations for these two columns, and therefore, every row would be in it’s own group (note `# Groups: gear, carb [11]`

in the `tibble`

output). Therefore, you are calculating `ntile`

of one element for every group, and the result will of course be 1.

If you don’t include the `.groups = "keep"`

argument, the last grouping variable will be dropped (`carb`

will be dropped), and you can see rank per `gear`

(note `# Groups: gear [3]`

).

```
library(dplyr)
mtcars %>%
group_by(gear,carb) %>%
summarise(total = sum(wt)) %>%
mutate(rank = ntile(total, 5))
# A tibble: 11 × 4
# Groups: gear [3]
gear carb total rank
<dbl> <dbl> <dbl> <int>
1 3 1 9.14 1
2 3 2 14.2 3
3 3 3 11.6 2
4 3 4 23.4 4
5 4 1 8.29 1
6 4 2 10.7 2
7 4 4 12.4 3
8 5 2 3.65 4
9 5 4 3.17 2
10 5 6 2.77 1
11 5 8 3.57 3
```