如何在 R 中使用 dplyr 基于组和子组对行求和？

Question

我的数据框有 2 个分类变量，其中一个的层次结构比另一个低。我想使用 dplyr.

对子类别中所有行的数值求和
提前感谢所有可以帮助我的人！

这是我开始的数据框：

transportation <- data.frame( Country = c("A", "A", "A", "B", "B", "B"), Mode = c("Car", "Train", "Plane", "Car", "Train", "Plane"), Energy = c(10000, 9000, 20000, 200000, 160000, 450000) )

这是我想要结束的数据框：

country_sum <- data.frame( Country = c("A", "A", "A", "B", "B", "B"), Mode = c("Car", "Train", "Plane", "Car", "Train", "Plane"), Energy = c(10000, 9000, 20000, 200000, 160000, 450000), country_sum = c(39000, 39000, 39000, 810000, 810000, 810000) )

Answer 1

首先按 Country 分组，然后 mutate 与 sum:

library(dplyr)

transportation %>% 
  group_by(Country) %>% 
  mutate(country_sum = sum(Energy))

 Country Mode  Energy country_sum
  <chr>   <chr>  <dbl>       <dbl>
1 A       Car    10000       39000
2 A       Train   9000       39000
3 A       Plane  20000       39000
4 B       Car   200000      810000
5 B       Train 160000      810000
6 B       Plane 450000      810000

Answer 2

使用 ave.

dplyr::mutate(transportation, c_sum=ave(Energy, Country, FUN=sum))
#   Country  Mode Energy  c_sum
# 1       A   Car  10000  39000
# 2       A Train   9000  39000
# 3       A Plane  20000  39000
# 4       B   Car 200000 810000
# 5       B Train 160000 810000
# 6       B Plane 450000 810000

如何在 R 中使用 dplyr 基于组和子组对行求和？

How to sum rows based on group and sub-group using dplyr in R?

r

dplyr