如何使用dplyr来总结不符合组的值 [英] How to summarize value not matching the group using dplyr

问题描述

我想对属于该行组以外的组的行进行求和。例如使用此样本数据

I want to sum values of rows which belongs to group other than the row's group. For example using this sample data

> df <- data.frame(id=1:5, group=c("A", "A", "B", "B", "A"), val=seq(9, 1, -2))
> df
  id group val
1  1     A   9
2  2     A   7
3  3     B   5
4  4     B   3
5  5     A   1

按 dplyr 按小组汇总

> df %>% group_by(group) %>% summarize(sumval = sum(val))
Source: local data frame [2 x 2]

   group sumval
  (fctr)  (dbl)
1      A     17
2      B      8

什么我想要的是属于组A的行的值使用不是组A的 sumval 。最终结果是

What I want is the value for rows belonging to group A to use sumval of not group A. i.e. the final result is

  id group val notval
1  1     A   9      8
2  2     A   7      8
3  3     B   5     17
4  4     B   3     17
5  5     A   1      8

有没有办法在 dplyr ？最重要的是在单链中？

Is there a way to do this in dplyr? Preferrably in a single chain?

推荐答案

@akrun答案是最好的。但是，如果你想在 dplyr 中做，这是一个圆滑的方式。

@akrun answers are best. But if you want to do in dplyr, this is a round about way.

df <- data.frame(id=1:5, group=c("A", "A", "B", "B", "A"), val=seq(9, 1, -2))



    df %>% mutate(TotalSum = sum(val)) %>% group_by(group) %>%
 mutate(valsumval = TotalSum - sum(val))

Source: local data frame [5 x 5]
Groups: group [2]

         id  group   val TotalSum valsumval
      (int) (fctr) (dbl)    (dbl)     (dbl)
    1     1      A     9       25         8
    2     2      A     7       25         8
    3     3      B     5       25        17
    4     4      B     3       25        17
    5     5      A     1       25         8

即使有两个以上的组也是如此。

This also works even if there are more than two groups.

另外这个工作

df %>% group_by(group) %>% mutate(notval = sum(df$val)- sum(val))

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