Using the package dplyr and the function sample_frac
it is possible to sample a percentage from every group. What I need is to first sort the elements in every group and then select top x% from every group?
There is a function top_n
, but here I can only determine the number of rows, and I need a relative value.
For example the following data is grouped by gear and sorted by wt
within 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 top 20 % within each gear group.
It would be very nice if the solution could be integrated with dplyr's group_by
function.
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
I know this is coming late, but might help someone now. dplyr has a new function top_frac
library(dplyr)
mtcars %>%
select(gear, wt) %>%
group_by(gear) %>%
arrange(gear, wt) %>%
top_frac(n = 0.2,wt = wt)
Here n is the fraction of rows to return and wt is the variable to be used for ordering.
The output is as below.
gear wt
3 5.250
3 5.345
3 5.424
4 3.440
4 3.440
5 3.570
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