"Total score" based on multiple "above/below median values" - r

Question

I am new to R and I have a problem that I simply cant find the solution to. I have tried reading through older posts etc. but I can't figure out how it could/should be done. I hope that some of you might be able to help.
Using the mtcars dataset as an example,
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
I wish to assign the cars a value (e.g. 1) if for instance the hp valvue is above the median and 0 if below. This could be called "hp_index".
I would do the same for lets say cyl, disp and drat, and then, I would like to assign the cars an "index_score" where a car for instance would be given the value 1 if a minimum of 3 out of the 4 hp, cyl, disp and drat is above median (that is, if 3 or 4 out of the 4 "hp_index", "cyl_index", "disp_index" and "drat_index" is 1).
Once again, I really hope that some of you might be able to help!
Thanks in advance, and have a nice day!

Answer 1

here's a tidyverse solution:
library(tidyverse)
mtcars %>%
mutate(across(c(hp, cyl, disp, drat), .fns = ~if_else(.x >= median(.x), 1, 0), .names = "{.col}_index"),
index_score = apply(across(c(hp_index, cyl_index, disp_index, drat_index)), 1, sum),
index_score = if_else(index_score >= 3, 1, 0))
Note: I created the conditions in a way that I split with >= median and < median. If you only use > and < there could be edge cases with missings if the row has exactly the median.
First six cases:
mpg cyl disp hp drat wt qsec vs am gear carb hp_index cyl_index disp_index drat_index index_score
1 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4 0 1 0 1 0
2 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4 0 1 0 1 0
3 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1 0 0 0 1 0
4 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 0 1 1 0 0
5 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2 1 1 1 0 1
6 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1 0 1 1 0 0

Answer 2

Using dplyr :
library(dplyr)
cols <- c('cyl', 'disp', 'drat', 'hp')
mtcars %>%
mutate(across(cols, list(index = ~+(.x > median(.x))))) %>%
mutate(index_score = +(rowSums(select(., ends_with('index'))) >= 3)) -> result
result
Used select(., ends_with('index')) in rowSums assuming there are no other columns that end with index in your actual dataset apart from the newly created ones with across.

Answer 3

In this case based on all the columns, otherwise specific columns can be selected
mtcars$index=rowSums(
sapply(mtcars,function(x){
ifelse(x>median(x),1,0)
})
)
mpg cyl disp hp drat wt qsec vs am gear carb index
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 4
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 4
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 5
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 4
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 4
...
from here you can do another ifelse on the "index" column to decide whether it be 0 or 1.
To use different filters for columns, as you proposed
rowSums(
cbind(
sapply(mtcars[c("cyl", "disp", "drat")],function(x){ifelse(x>median(x),1,0)}),
sapply(mtcars["hp"],function(x){ifelse(x<median(x),1,0)})
)
)