I have seen a variety of posts that detail how to do a similar function, but I have yet to find one that divides all rows by a reference row while excluding the reference row itself.
Here is an example set of data with required packages:
library(tidyverse)
library(janitor)
d <- tibble(
level = as.factor(c(1:10)),
var_1 = sample(c(1:20), 10),
var_2 = sample(c(1:30), 10),
var_3 = sample(c(1:40), 10),
var_4 = sample(c(1:50), 10),
)
In the following code, I am dividing each row by the Total row generated by adorn_totals():
d %>%
adorn_totals("row") %>%
mutate_at(vars(-level), funs(round(./.[11]*100, 2)))
Here is the output:
level var_1 var_2 var_3 var_4
1 3.66 13.89 6.0 6.50
2 10.98 11.11 0.5 8.94
3 4.88 7.64 14.0 15.45
4 6.10 18.06 16.0 7.72
5 18.29 13.19 10.0 9.35
6 14.63 10.42 11.5 3.25
7 2.44 6.25 12.5 19.51
8 8.54 11.81 13.5 4.07
9 23.17 3.47 1.0 20.33
10 7.32 4.17 15.0 4.88
Total 100.00 100.00 100.0 100.00
But, I want to calculate these proportions of the total without impacting the Total row itself. Below I've attached the desired output with the row totals untouched while the rest of the rows have been mutated per my function.
level var_1 var_2 var_3 var_4
1 3.66 13.89 6.0 6.50
2 10.98 11.11 0.5 8.94
3 4.88 7.64 14.0 15.45
4 6.10 18.06 16.0 7.72
5 18.29 13.19 10.0 9.35
6 14.63 10.42 11.5 3.25
7 2.44 6.25 12.5 19.51
8 8.54 11.81 13.5 4.07
9 23.17 3.47 1.0 20.33
10 7.32 4.17 15.0 4.88
Total 82 144 200 246
Thanks for your help!
It seems like adorn_percentages does the same thing as your custom function.
d %>%
adorn_percentages("col") %>%
mutate_at(vars(-level), ~round(.*100,2)) %>%
bind_rows(
d %>% adorn_totals("row") %>% slice(11)
)