Addition of specific rows in a dataframe - r

Question

I'm trying to add specific row of a data frame together.
And short of using grepl to find lines and then rbinding them to the bottom, I'm not sure if there's a better way to do this.
this is my input df:
input = structure(list(
V1 = c("Sales", "Sales", "Sales", "Sales", "Sales","Sales"),
V2 = c("Johnny", "Meg", "Fred", "Johnny", "Meg", "Fred"),
V3 = c("Australia", "Australia", "Australia", "NZ", "NZ","NZ"),
V4 = c(154L, 1898L, 175L, 1235L, 23L, 255L)), row.names = c(NA,6L),
class = "data.frame")
and this is my expected output:
structure(list(
V1 = c("Sales", "Sales", "Sales", "Sales", "Sales",
"Sales", "Sales", "Sales", "Sales", "Sales", "Sales", "Sales"),
V2 = c("Johnny", "Meg", "Fred", "Johnny", "Meg", "Fred", "Johnny + Fred",
"Meg + Fred", "Johnny + Meg + Fred", "Johnny + Fred", "Meg + Fred",
"Johnny + Meg + Fred"),
V3 = c("Australia", "Australia", "Australia", "NZ",
"NZ", "NZ", "Australia", "Australia", "Australia", "NZ", "NZ", "NZ"),
V4 = c(154L, 1898L, 175L, 1235L, 23L, 255L, 329L, 2073L, 2227L, 1490L, 278L, 1513L)),
class = "data.frame", row.names = c(NA, -12L)
)
I would've thought there's a better way to there's a better way of adding these rows that filtering and then adding, and then joining etc.
Can anyone point me in the right direction of what I should be looking for?

Answer 1

I solve the problem using combn
Data input part
input = structure(list(
V1 = c("Sales", "Sales", "Sales", "Sales", "Sales","Sales"),
V2 = c("Johnny", "Meg", "Fred", "Johnny", "Meg", "Fred"),
V3 = c("Australia", "Australia", "Australia", "NZ", "NZ","NZ"),
V4 = c(154L, 1898L, 175L, 1235L, 23L, 255L)), row.names = c(NA,6L),
class = "data.frame")
structure(list(
V1 = c("Sales", "Sales", "Sales", "Sales", "Sales",
"Sales", "Sales", "Sales", "Sales", "Sales", "Sales", "Sales"),
V2 = c("Johnny", "Meg", "Fred", "Johnny", "Meg", "Fred", "Johnny + Fred",
"Meg + Fred", "Johnny + Meg + Fred", "Johnny + Fred", "Meg + Fred",
"Johnny + Meg + Fred"),
V3 = c("Australia", "Australia", "Australia", "NZ",
"NZ", "NZ", "Australia", "Australia", "Australia", "NZ", "NZ", "NZ"),
V4 = c(154L, 1898L, 175L, 1235L, 23L, 255L, 329L, 2073L, 2227L, 1490L, 278L, 1513L)),
class = "data.frame", row.names = c(NA, -12L)
)
Solution
library(dplyr)
TT = unique(input$V2)
> TT
[1] "Johnny" "Meg" "Fred"
comb2 = combn(TT,2,simplify = FALSE)
> comb2
[[1]]
[1] "Johnny" "Meg"
[[2]]
[1] "Johnny" "Fred"
[[3]]
[1] "Meg" "Fred"
comb3 = combn(TT,3,simplify = FALSE)
> comb3
[[1]]
[1] "Johnny" "Meg" "Fred"
result = function(data){
purrr::map_df(lapply(data,function(x){paste(x,collapse = '|')}), function(x){
df = input[grepl(x,input$V2),] %>% group_by(V3)%>%summarize(V1= 'Sales',
V2= paste(V2,collapse = '+'),
V4= sum(V4))
return(df)
}
)
}
Result
result(comb2)
# A tibble: 6 x 4
V3 V1 V2 V4
<chr> <chr> <chr> <int>
1 Australia Sales Johnny+Meg 2052
2 NZ Sales Johnny+Meg 1258
3 Australia Sales Johnny+Fred 329
4 NZ Sales Johnny+Fred 1490
5 Australia Sales Meg+Fred 2073
6 NZ Sales Meg+Fred 278
result(comb3)
# A tibble: 2 x 4
V3 V1 V2 V4
<chr> <chr> <chr> <int>
1 Australia Sales Johnny+Meg+Fred 2227
2 NZ Sales Johnny+Meg+Fred 1513
finalResult = bind_rows(A,B,input) %>%
select(V1,V2,V3,V4) %>% filter(! V2 %in% c('Johnny+Meg'))
> finalResult
# A tibble: 12 x 4
V1 V2 V3 V4
<chr> <chr> <chr> <int>
1 Sales Johnny+Fred Australia 329
2 Sales Johnny+Fred NZ 1490
3 Sales Meg+Fred Australia 2073
4 Sales Meg+Fred NZ 278
5 Sales Johnny+Meg+Fred Australia 2227
6 Sales Johnny+Meg+Fred NZ 1513
7 Sales Johnny Australia 154
8 Sales Meg Australia 1898
9 Sales Fred Australia 175
10 Sales Johnny NZ 1235
11 Sales Meg NZ 23
12 Sales Fred NZ 255

Answer 2

Using tidyverse we can first split the dataframe based on V3 then create combination of names and add sum to create a new tibble and bind it to the original dataframe.
library(tidyverse)
input %>%
bind_rows(input %>%
group_split(V3) %>%
map_dfr(function(x) map_dfr(2:nrow(x), ~tibble(
V1 = first(x$V1),
V2 = combn(x$V2, ., paste, collapse = " + "),
V3 = first(x$V3),
V4 = combn(x$V4, .,sum)) %>%
filter(grepl("\\bFred\\b", V2)))))
# V1 V2 V3 V4
#1 Sales Johnny Australia 154
#2 Sales Meg Australia 1898
#3 Sales Fred Australia 175
#4 Sales Johnny NZ 1235
#5 Sales Meg NZ 23
#6 Sales Fred NZ 255
#7 Sales Johnny + Fred Australia 329
#8 Sales Meg + Fred Australia 2073
#9 Sales Johnny + Meg + Fred Australia 2227
#10 Sales Johnny + Fred NZ 1490
#11 Sales Meg + Fred NZ 278
#12 Sales Johnny + Meg + Fred NZ 1513
Using the same logic but in base R, we can do
rbind(input, do.call(rbind, lapply(split(input, input$V3), function(x)
do.call(rbind, lapply(2:nrow(x), function(y)
subset(data.frame(V1 = x$V1[1],
V2 = combn(x$V2, y, paste, collapse = " + "),
V3 = x$V3[1],
V4 = combn(x$V4, y, sum)),
grepl("\\bFred\\b", V2)))))))