Here is my data:
>my.cut <- cut(my.variable, breaks = c(-Inf, -0.5, -0.25, -0.1, 0, 0.02, 0.05, 0.15, 0.3, 0.5, 1, Inf), right = FALSE)
>levels(my.cut)
"[-Inf,-0.5)" "[-0.5,-0.25)" "[-0.25,-0.1)" "[-0.1,0)" "[0,0.02)" "[0.02,0.05)" "[0.05,0.15)" "[0.15,0.3)" "[0.3,0.5)" "[0.5,1)" "[1, Inf)"
Expected result:
>levels(my.cut)
"[-Inf,-0.5)" "[-0.5,-0.25)" "[-0.25,-0.1)" "[-0.1,0)" "0" "(0,0.02)" "[0.02,0.05)" "[0.05,0.15)" "[0.15,0.3)" "[0.3,0.5)" "[0.5,1)" "[1, Inf)"
In the expected result, there is single figure 0 which I only want to choose the my.variable==0, but with the formula of the my.cut, there is no single 0 cause breaks can only be used for interval. So how could I do?
Hope to get your answer soon! Thanks!
You could explicitly put each value into a group. This is more flexible, but also a lot more verbose.
One way of doing this could be to define a bespoke cut function and then apply it to every element of your vector.
my.variable <- rnorm(100)
bespoke_cut <- function(value){
if (value < 0.1) return('[-Inf, 0.1)')
if (value < 0) return('[0.1, 0)')
if (value == 0) return('0')
return('(0, Inf]')
}
my.cut <- sapply(my.variable, bespoke_cut)
my.cut <- factor(my.cut)
I've only done a few of the groupings you wanted, but I think it should be apparent how to add extra groups.