I have a list l, which has the following features:
- It has 3 elements
- Each element is a numeric vector of length 5
- Each vector contains numbers from 1 to 5
l = list(a = c(2, 3, 1, 5, 1), b = c(4, 3, 3, 5, 2), c = c(5, 1, 3, 2, 4))
I want to do two things:
First
I want to know how many times each number occurs in the entire list and I want each result in a vector (or any form that can allow me to perform computations with the results later):
Code 1:
> a <- table(sapply(l, "["))
> x <- as.data.frame(a)
> x
Var1 Freq
1 1 3
2 2 3
3 3 4
4 4 2
5 5 3
Is there anyway to do it without using the table() function. I would like to do it "manually". I try to do it right below.
Code 2: (I know this is not very efficient!)
x <- data.frame(
"1" <- sum(sapply(l, "[")) == 1
"2" <- sum(sapply(l, "[")) == 2
"3" <- sum(sapply(l, "[")) == 3
"4" <- sum(sapply(l, "[")) == 4
"5" <- sum(sapply(l, "[")) == 5)
I tried the following, but I did not work. I actually did not understand the result.
> sapply(l, "[") == 1:5
a b c
[1,] FALSE FALSE FALSE
[2,] FALSE FALSE FALSE
[3,] FALSE TRUE TRUE
[4,] FALSE FALSE FALSE
[5,] FALSE FALSE FALSE
> sum(sapply(l, "[") == 1:5)
[1] 2
Second
Now, I would like to get the number of times each number appears in the list, but now in each element $a, $b and $c. I thought about using the lapply() but I don't know how exactly. Following is what I tried, but it is inefficient just like Code 2:
lapply(l, function(x) sum(x == 1))
lapply(l, function(x) sum(x == 2))
lapply(l, function(x) sum(x == 3))
lapply(l, function(x) sum(x == 4))
lapply(l, function(x) sum(x == 5))
What I get with these 5 lines of code are 5 lists of 3 elements each containing a single numeric value. For example, the second line of code tells me how many times number 2 appears in each element of l.
Code 3:
> lapply(l, function(x) sum(x == 2))
$a
[1] 1
$b
[1] 1
$c
[1] 1
What I would like to obtain is a list with three elements containing all the information I am looking for.
Please, use the references "Code 1", "Code 2" and "Code 3" in your answers. Thank you very much.
Answer
Just use as.data.frame(l) for the second part and table(unlist(l)) for the first.
> table(unlist(l))
1 2 3 4 5
3 3 4 2 3
> data.frame(lapply(l, tabulate))
a b c
1 2 0 1
2 1 1 1
3 1 2 1
4 0 1 1
5 1 1 1`