自定义分组的dplyr函数(sample_n) [英] custom grouped dplyr function (sample_n)

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本文介绍了自定义分组的dplyr函数(sample_n)的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我正在尝试以分组方式将采样函数应用于数据帧,在该数据帧中,应从每个组(如果组大小小于n 或所有组成员)中采样n个样本。

I am trying to apply a sampling function in a grouped fashion to a data frame, where it should sample n samples from each group, or all group members if the group size is smaller than n.

使用dplyr,我首先尝试

Using dplyr, I first tried

library(dplyr)
mtcars %>% group_by(cyl) %>% sample_n(2)

此当n小于所有组的大小时有效,但是当我选择大于组的大小n时不接受完整的组(请注意,一个圆柱组中有7辆车):

This works when n is smaller than all the group sizes but does not take the full group when I choose n larger than the group size (note that there are 7 cars in one of the cyl groups):

mtcars %>% group_by(cyl) %>% sample_n(8)
Error: `size` must be less or equal than 7 (size of data), 
set `replace` = TRUE to use sampling with replacement

通过创建一个适应的group_n函数来解决此问题,例如:

I tried to solve this by creating an adapted group_n function like so:

sample_n_or_all <- function(tbl, n) {
  if (nrow(tbl) < n)return(tbl)
  sample_n(tbl, n)
}

但使用我的自定义函数( mtcars%>%group_by(cyl)% >%sample_n_or_all(8))会产生相同的错误。

but using my custom function (mtcars %>% group_by(cyl) %>% sample_n_or_all(8)) generates the same error.

关于如何调整函数的任何建议,以便将其应用于每个函数组中的?还是该问题的另一种解决方案?

Any suggestions how I can adapt my function so I can apply it to each of the groups? Or another solution to the problem?

推荐答案

我们可以检查组中的行数并将值传递给 sample_n

We could check the number of rows in the group and pass the value to sample_n accordingly.

library(dplyr)
n <- 8

temp <- mtcars %>% group_by(cyl) %>% sample_n(if(n() < n) n() else n) 
temp

#    mpg   cyl  disp    hp  drat    wt  qsec    vs    am  gear  carb
#   <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
# 1  21.4     4 121     109  4.11  2.78  18.6     1     1     4     2
# 2  27.3     4  79      66  4.08  1.94  18.9     1     1     4     1
# 3  24.4     4 147.     62  3.69  3.19  20       1     0     4     2
# 4  22.8     4 108      93  3.85  2.32  18.6     1     1     4     1
# 5  26       4 120.     91  4.43  2.14  16.7     0     1     5     2
# 6  33.9     4  71.1    65  4.22  1.84  19.9     1     1     4     1
# 7  30.4     4  75.7    52  4.93  1.62  18.5     1     1     4     2
# 8  30.4     4  95.1   113  3.77  1.51  16.9     1     1     5     2
# 9  21       6 160     110  3.9   2.62  16.5     0     1     4     4
#10  17.8     6 168.    123  3.92  3.44  18.9     1     0     4     4
# … with 13 more rows

之后,我们可以检查每个组中的行数。

We can check number of rows in each group after that.

table(temp$cyl)

#4 6 8 
#8 7 8 

table(mtcars$cyl)

# 4  6  8 
#11  7 14 

这篇关于自定义分组的dplyr函数(sample_n)的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持IT屋!

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