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 walkI 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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