使用 dplyr 在排除当前观察的同时计算组平均值

本文介绍了使用 dplyr 在排除当前观察的同时计算组平均值的处理方法，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

使用 dplyr(最好)，我试图计算每个观察的组平均值，同时从组中排除该观察.

Using dplyr (preferably), I am trying to calculate the group mean for each observation while excluding that observation from the group.

看起来这应该可以通过 rowwise() 和 group_by() 的组合来实现，但是这两个函数不能同时使用.

It seems that this should be doable with a combination of rowwise() and group_by(), but both functions cannot be used simultaneously.

给定这个数据框:

df <- data_frame(grouping = rep(LETTERS[1:5], 3), value = 1:15) %>% arrange(grouping) df #> Source: local data frame [15 x 2] #> #> grouping value #> (chr) (int) #> 1 A 1 #> 2 A 6 #> 3 A 11 #> 4 B 2 #> 5 B 7 #> 6 B 12 #> 7 C 3 #> 8 C 8 #> 9 C 13 #> 10 D 4 #> 11 D 9 #> 12 D 14 #> 13 E 5 #> 14 E 10 #> 15 E 15

我想获得每个观察的组均值，该观察被排除在组之外，结果:

I'd like to get the group mean for each observation with that observation excluded from the group, resulting in:

#> grouping value special_mean #> (chr) (int) #> 1 A 1 8.5 # i.e. (6 + 11) / 2 #> 2 A 6 6 # i.e. (1 + 11) / 2 #> 3 A 11 3.5 # i.e. (1 + 6) / 2 #> 4 B 2 9.5 #> 5 B 7 7 #> 6 B 12 4.5 #> 7 C 3 ...

我尝试将 rowwise() 嵌套在由 do() 调用的函数中，但没有让它工作，如下所示:

I've attempted nesting rowwise() inside a function called by do(), but haven't gotten it to work, along these lines:

special_avg <- function(chunk) { chunk %>% rowwise() #%>% # filter or something...? } df %>% group_by(grouping) %>% do(special_avg(.))

推荐答案

无需定义自定义函数，而是我们可以简单地将组的所有元素相加，减去当前值，然后除以每组的元素数减去1.

No need to define a custom function, instead we could simply sum all elements of the group, subtract the current value, and divide by number of elements per group minus 1.

df %>% group_by(grouping) %>% mutate(special_mean = (sum(value) - value)/(n()-1)) # grouping value special_mean # (chr) (int) (dbl) #1 A 1 8.5 #2 A 6 6.0 #3 A 11 3.5 #4 B 2 9.5 #5 B 7 7.0