mtcars %>% select(mpg, cyl) %>% group_by(cyl) %>% arrange(mpg) %>% slice(8)
outputs
mpg cyl
<dbl> <dbl>
1 30.4 4
2 15.2 8
As you can see, it does not produce a row for 6 cylinders - what is the recommended way to keep all the groups, even if combine is empty?
To quickly select a row from each group, keeping NA
s, you can subset inside summarise_all
:
mtcars %>% group_by(cyl) %>%
arrange(mpg) %>%
summarise_all(funs(.[8]))
## # A tibble: 3 × 11
## cyl mpg disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 30.4 75.7 52 4.93 1.615 18.52 1 1 4 2
## 2 6 NA NA NA NA NA NA NA NA NA NA
## 3 8 15.2 304.0 150 3.15 3.435 17.30 0 0 3 2
However, @Frank is right above; it won't extend nicely to subsetting to multiple rows in this format because summarise
demands a single result row for each group. To subset, say, rows 7 and 8 of each group, use a list column and unnest with tidyr::unnest
:
library(tidyverse)
mtcars %>% group_by(cyl) %>%
arrange(mpg) %>%
summarise_all(funs(list(.[7:8]))) %>%
unnest()
## # A tibble: 6 × 11
## cyl mpg disp hp drat wt qsec vs am gear carb
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 27.3 79.0 66 4.08 1.935 18.90 1 1 4 1
## 2 4 30.4 75.7 52 4.93 1.615 18.52 1 1 4 2
## 3 6 21.4 258.0 110 3.08 3.215 19.44 1 0 3 1
## 4 6 NA NA NA NA NA NA NA NA NA NA
## 5 8 15.2 275.8 180 3.07 3.780 18.00 0 0 3 3
## 6 8 15.2 304.0 150 3.15 3.435 17.30 0 0 3 2
A more concise version with purrr::dmap
returns the same thing:
mtcars %>% group_by(cyl) %>%
arrange(mpg) %>%
dmap(~.x[7:8])
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