I'm attempting to mutate three numeric columns into percentages based on the sum of each column, using mutate(across(.cols = c(...))). My usual method of doing this for one column works very well:
mutate(`Percentage`= ((`Count`/sum(.$`Count`))*100))
When I apply a similar principle to a multi-column mutate call using .x or . to stand in for all called values, it instead divides each value by itself. Where am I going wrong?
# Sample Code
test<-data.frame(fruit=c("Apples","Pears","Bananas"),
`John`=c(1,13,34),
`Jacob`=c(5,9,2))%>%
group_by(`fruit`)%>%
mutate(`Total`=sum(`John`,`Jacob`))
# A tibble: 3 × 4
# Groups: fruit [3]
fruit John Jacob Total
<chr> <dbl> <dbl> <dbl>
1 Apples 1 5 6
2 Pears 13 9 22
3 Bananas 34 2 36
fruiteaten<-test%>%
mutate(across(.cols=c(`John`,
`Jacob`,
`Total`), .fns = ~ ((.x/sum(.x))*100)))
# Output
# A tibble: 3 × 4
# Groups: fruit [3]
fruit John Jacob Total
<chr> <dbl> <dbl> <dbl>
1 Apples 100 100 100
2 Pears 100 100 100
3 Bananas 100 100 100
# Desired Output
fruit John Jacob Total
1 Apples 0.02 0.31 0.09
2 Pears 0.27 0.56 0.34
3 Bananas 0.70 0.12 0.56
You should not be grouping:
test |>
ungroup() |>
mutate(across(-fruit, \(x) x / sum(x) * 100))
# A tibble: 3 × 4
fruit John Jacob Total
<chr> <dbl> <dbl> <dbl>
1 Apples 2.08 31.2 9.38
2 Pears 27.1 56.2 34.4
3 Bananas 70.8 12.5 56.2
P.s. you only need to use `backticks` for variables that are not legal names, such as names with spaces or illegal characters.