# R - Function That Dichotomizes Certain Columns Of A Data Frame Based On Different Thresholds

## 24 March 2022 - 1 answer

I am trying to create a function that dichotomizes certain defined columns of a data frame based on different values depending on the column.

For example, in the following data frame with conditions A, B, C and D:

``````A <- c(0, 2, 1, 0, 2, 1, 0, 0, 1, 2)
B <- c(0, 1, 1, 1, 0, 0, 0, 1, 1, 0)
C <- c(0, 0, 0, 1, 1, 1, 1, 1, 1, 1)
D <- c(0, 0, 3, 1, 2, 1, 4, 0, 3, 0)
Data <- data.frame(A, B, C, D)
``````

I would like the function to dichotomize the conditions that I select [e.g. A, B, D] and dichotomize them based on thresholds that I assign [e.g. 2 for A, 1 for B, 3 for D].

I would like the dichotomized columns to be added to the data frame with different names [e.g. A_dich, B_dich, D_dich].

The final data frame should look like this (you will notice B is already dichotomized, which is fine, it should just be treated equally and added):

``````   A B C D A_dicho B_dicho D_dicho
1  0 0 0 0       0       0       0
2  2 1 0 0       1       1       0
3  1 1 0 3       0       1       1
4  0 1 1 1       0       1       0
5  2 0 1 2       1       0       0
6  1 0 1 1       0       0       0
7  0 0 1 4       0       0       1
8  0 1 1 0       0       1       0
9  1 1 1 3       0       1       1
10 2 0 1 0       1       0       0
``````

Could someone help me? Many thanks in advance.

Make a little threshold vector specifying the values, then `Map` it to the columns:

``````thresh <- c("A"=2, "B"=1, "D"=3)
Data[paste(names(thresh), "dicho", sep="_")] <- Map(
\(d,th) as.integer(d >= th), Data[names(thresh)], thresh
)
Data
##   A B C D A_dicho B_dicho D_dicho
##1  0 0 0 0       0       0       0
##2  2 1 0 0       1       1       0
##3  1 1 0 3       0       1       1
##4  0 1 1 1       0       1       0
##5  2 0 1 2       1       0       0
##6  1 0 1 1       0       0       0
##7  0 0 1 4       0       0       1
##8  0 1 1 0       0       1       0
##9  1 1 1 3       0       1       1
##10 2 0 1 0       1       0       0
``````