如何为3组添加一些列值？ [英] how to add some value of columns with respect of 3 groups?
问题描述
我有3列：SAMPN，PERNO，循环。以及与3种模式相对应的实用程序。角豆和步行
我想添加具有相同SAMPN，PERNO，循环的行的实用程序。对于car.car，bus.bus，walk.walk，walk.bus和bus.walk
I have 3 column : SAMPN,PERNO, loop. and utilities corresponding to 3 modes. carobs and walk I want to add utility of rows whose have the same SAMPN,PERNO, loop. for car.car, bus.bus, walk.walk, walk.bus and bus.walk
示例
SAMPN PERNO PLANO loop walk car bus MODE1
<chr> <fct> <fct> <fct> <chr> <chr> <chr> <fct>
1 " 4" 1 " 2" 2 -0.990765697239748 2.09989661853416 -0.92177603128108 2
2 " 4" 1 " 7" 2 0.11385013993979 1.09436996098927 -0.534987482042767 2
3 " 4" 2 " 2" 2 0.500507525721786 0.924888419124695 -0.376370439308976 2
4 " 4" 2 " 7" 2 -0.299078042202768 1.54226436622111 -0.289562610169849 2
5 " 6" 1 " 2" 2 -0.991897610390741 1.58114646818508 -0.973443199067661 2
6 " 6" 1 " 3" 2 -1.05376527366975 1.61719511863015 -0.832468269682489 2
在SAMPN 4中，第一行的内容相同SAMPN，PERNO和loop，所以我将添加这两行的交叉实用程序。
in SAMPN 4, 2 first row have same SAMPN , PERNO and loop so I will add the crossponding utility of these 2 rows.
car.car 2.09989661853416+1.09436996098927 = 3.194267
bus.bus -0.92177603128108+-0.534987482042767 =-1.456764
walk.walk -0.990765697239748+0.11385013993979=-0.8769156
walk.bus -0.92177603128108+-0.534987482042767=-1.456764
bus.walk -0.92177603128108+ 0.11385013993979 =-0.8079259
与其他人相同。
我知道是否要在每行中添加值我可以使用它：但是如何在不同的行中添加实用工具？
I know if I wanted to add the value in each row I could use this: but how to add utility in different rows?
kl<-r %>%
+ group_by(SAMPN, PERNO,loop) %>%
+ mutate(car.car = car+car, walk.walk=walk+walk, bus.bus=bus+bus, walk.bus=walk+bus, bus.walk=bus+walk)
数据：
structure(list(SAMPN = c(" 4", " 4", " 4", " 4",
" 6", " 6"), PERNO = structure(c(1L, 1L, 2L, 2L, 1L, 1L
), .Label = c("1", "2", "3", "4", "5", "6", "7"), class = "factor"),
PLANO = structure(c(1L, 6L, 1L, 6L, 1L, 2L), .Label = c(" 2",
" 3", " 4", " 5", " 6", " 7", " 8", " 9", "10", "11", "12",
"13", "14", "15", "16", "17", "18", "19", "20", "21", "23",
"24"), class = "factor"), loop = structure(c(2L, 2L, 2L,
2L, 2L, 2L), .Label = c("1", "2", "3", "4", "5", "6", "7",
"8"), class = "factor"), walk = c("-0.990765697239748", "0.11385013993979",
"0.500507525721786", "-0.299078042202768", "-0.991897610390741",
"-1.05376527366975"), car = c("2.09989661853416", "1.09436996098927",
"0.924888419124695", "1.54226436622111", "1.58114646818508",
"1.61719511863015"), bus = c("-0.92177603128108", "-0.534987482042767",
"-0.376370439308976", "-0.289562610169849", "-0.973443199067661",
"-0.832468269682489"), MODE1 = structure(c(2L, 2L, 2L, 2L,
2L, 2L), .Label = c("1", "2", "3", "4"), class = "factor")), row.names = c(NA,
-6L), groups = structure(list(SAMPN = c(" 4", " 4", " 6"
), PERNO = structure(c(1L, 2L, 1L), .Label = c("1", "2", "3",
"4", "5", "6", "7"), class = "factor"), loop = structure(c(2L,
2L, 2L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8"), class = "factor"),
.rows = list(1:2, 3:4, 5:6)), row.names = c(NA, -3L), class = c("tbl_df",
"tbl", "data.frame"), .drop = TRUE), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"))
仅输出前两行：
SAMPN PERNO PLANO loop car.car bus.bus walk.walk walk.bus bus.walk MODE1
1 " 4" 1 " 2" 2 3.194267 -1.456764 -0.8769156 -1.456764 -0.8079259 2
2 " 4" 1 " 7" 2 3.194267 -1.456764 -0.8769156 -1.456764 -0.8079259 2
推荐答案
如果需要为特定组合创建，在 group_by 步骤之后，可以一个一列地创建列
If we need to create for specific combinations, after the group_by step, can create the columns one by one
library(dplyr)
df1 %>%
group_by(SAMPN, PERNO, loop) %>%
mutate_at(vars(walk:bus), as.numeric) %>%
mutate(walk.bus = first(walk) + last(bus),
bus.walk = first(bus) + last(walk),
walk.walk = sum(walk),
bus.bus = sum(bus),
car.car = sum(car))
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