Dplyr - Group and select TOP x%

Question

Using the dplyr package and function sample_frac, you can try the percentage of each group. Do I need to sort the elements in each group first and then select the top x% from each group?

There is a function top_n, but here I can determine the number of rows, and I need a relative value.

For example, the following data is grouped by gear and sorted by wtinside each group:

library(dplyr)
mtcars %>%
  select(gear, wt) %>%
  group_by(gear) %>%
  arrange(gear, wt)

    gear    wt
1   3   2.465
2   3   3.215
3   3   3.435
4   3   3.440
5   3   3.460
6   3   3.520
7   3   3.570
8   3   3.730
9   3   3.780
10  3   3.840
11  3   3.845
12  3   4.070
13  3   5.250
14  3   5.345
15  3   5.424
16  4   1.615
17  4   1.835
18  4   1.935
19  4   2.200
20  4   2.320
21  4   2.620
22  4   2.780
23  4   2.875
24  4   3.150
25  4   3.190
26  4   3.440
27  4   3.440
28  5   1.513
29  5   2.140
30  5   2.770
31  5   3.170
32  5   3.570

Now I would like to select the top 20% in each gear group.

It would be very nice if the solution could be integrated with the dplyr function group_by.

Answer 1

Or another option with dplyr:

mtcars %>% select(gear, wt) %>% 
  group_by(gear) %>% 
  arrange(gear, desc(wt)) %>% 
  filter(wt > quantile(wt, .8))

Source: local data frame [7 x 2]
Groups: gear [3]

   gear    wt
  (dbl) (dbl)
1     3 5.424
2     3 5.345
3     3 5.250
4     4 3.440
5     4 3.440
6     4 3.190
7     5 3.570

Answer 2

mtcars %>% 
  select(gear, wt) %>% 
  arrange(gear, desc(wt)) %>% 
  group_by(gear) %>% 
  slice(seq(n()*.2))

   gear    wt
  (dbl) (dbl)
1     3 5.424
2     3 5.345
3     3 5.250
4     4 3.440
5     4 3.440
6     5 3.570

"", " wt" desc().

Answer 3

, .

library(dplyr)

mtcars %>% select(gear, wt) %>% 
  group_by(gear) %>% 
  arrange(gear, wt) %>% 
  filter(row_number() / n() <= .2)

Answer 4

, , - . dplyr top_frac

  library(dplyr)
mtcars %>%
  select(gear, wt) %>%
  group_by(gear) %>%
  arrange(gear, wt) %>%
  top_frac(n = 0.2,wt = wt)

n - , wt - , .

.

gear wt 3 5.250 3 5.345 3 5.424
4 3.440 4 3.440 5 3.570