Use sapply to obtain a vector of lists - r

Consider the following list:
temp <- list(1, "a", TRUE)
We can use sapply to replicate the list:
> ts <- sapply(1:5, function(x) temp)
> ts
[,1] [,2] [,3] [,4] [,5]
id 1 1 1 1 1
grade "a" "a" "a" "a" "a"
alive TRUE TRUE TRUE TRUE TRUE
If I inspect the result using typeof, I obtain list. However, if I inspect it with sapply, I get this:
> sapply(ts, function(x) print(x))
[1] 1
[1] "a"
[1] TRUE
[1] 1
[1] "a"
[1] TRUE
[1] 1
[1] "a"
[1] TRUE
[1] 1
[1] "a"
[1] TRUE
[1] 1
[1] "a"
[1] TRUE
That is, when I inspect the same result with sapply, this vector of lists is treated as a matrix. Is there any workaround, or does R disallow a vector of lists in general? If the latter is the case, why do I get "list" from typeof?
PS: For my specific question, I understand the obvious solution of using lapply to switch to a list of lists. I am just curious and confused by R’s behavior.

The return of sapply(ts, function(x) print(x)) is still a list. Actually a list of 15 variables as 3 members of temp has been simplified and returned as 3 items (times 5 iterations). If you want something like lapply like output please try:
>ts <- sapply(1:5, function(x) temp, simplify = FALSE)
> ts
#[[1]]
#[[1]][[1]]
#[1] 1
#
#[[1]][[2]]
#[1] "a"
#
#[[1]][[3]]
#[1] TRUE
#.......
#.......
Or even you can try:
>ts <- sapply(1:5, function(x) as.data.frame(temp))

Related

mapply on pairs of elements in a lists in R

If I have a symmetric binary operator that I want to apply over the pairs of elements from a list, is there an easy way I can do this in R? I tried:
A <- list(1,2,3)
mapply(function(x,y) x+y, A,A)
but this only gives x[n]+y[n] for all n=1..N but I want x[n]+y[m] for all m=1..n, n=1..N returned as a list. outer(..) does that for m=1..N, n=1..N which involves redundant computation so I want to discount that.
Notice I don't want solution to this simple example. I need a general solution that works for non-numeric input as well. The thing I'm trying to do is like:
mapply(function(set_1, set_2) setequal(intersect(set_1, set_2), set_3), list_of_sets, list_of_sets)
In both cases addition and intersection are symmetric. In the first example, I expect list(3,4,5) from list(1+2,1+3,2+3). For the second case me input list_of_sets is:
> list_of_sets
[[1]]
numeric(0)
[[2]]
[1] 1
[[3]]
[1] 2
[[4]]
[1] 1 2
[[5]]
[1] 3
[[6]]
[1] 1 3
[[7]]
[1] 2 3
[[8]]
[1] 1 2 3
and set_3 being c(1,2) as a simple example.
You may use outer -
values <- c(1, 2, 3)
outer(values, values, `+`)
# [,1] [,2] [,3]
#[1,] 2 3 4
#[2,] 3 4 5
#[3,] 4 5 6
outer also works for non-numeric input. If the function that you want to apply is not vectorised you can use Vectorize. Since OP did not provide an example I have created one of my own.
list_of_sets_1 <- list(c('a', 'b', 'c'), c('a'))
list_of_sets_2 <- list(c('a', 'c'), c('a', 'b'))
fun <- function(x, y) intersect(x, y)
result <- outer(list_of_sets_1, list_of_sets_2, Vectorize(fun))
result
We need combn to do pairwise computation without redundancy
combn(A, 2, FUN = function(x) x[[1]] + x[[2]], simplify = FALSE)
-output
[[1]]
[1] 3
[[2]]
[1] 4
[[3]]
[1] 5
This will also work with non-numeric elements
list_of_sets <- list(c('a', 'b', 'c'), "a", c("a", "c"))
combn(list_of_sets, 2, FUN = function(x) Reduce(intersect, x), simplify = FALSE)
-output
[[1]]
[1] "a"
[[2]]
[1] "a" "c"
[[3]]
[1] "a"
We may also do
combn(list_of_sets, 2, FUN = function(x)
setequal(intersect(x[[1]], x[[2]]), set_3), simplify = FALSE)

Add positional index to a list

I would like to add a sequential element onto a list. Suppose I have the following list
lst <- list("A"=list(e1="a",e2="!"), "B"=list(e1="b", e2="#"))
$A
$A$e1
[1] "a"
$A$e2
[1] "!"
$B
$B$e1
[1] "b"
$B$e2
[1] "#"
I would like to append a e3 which is the position index of that element in the list so essentially I would like my list to be:
$A
$A$e1
[1] "a"
$A$e2
[1] "!"
$A$e3
[1] 1
$B
$B$e1
[1] "b"
$B$e2
[1] "#"
$B$e3
[1] 2
setNames(lapply(seq_along(lst), function(i){
temp = lst[[i]]
temp$e3 = i
temp
}), names(lst))
#$`A`
#$`A`$`e1`
#[1] "a"
#$`A`$e2
#[1] "!"
#$`A`$e3
#[1] 1
#$B
#$B$`e1`
#[1] "b"
#$B$e2
#[1] "#"
#$B$e3
#[1] 2
Here is a solution that doesn't assume that the sub-lists have the same known number of elements.
library("tidyverse")
library("glue")
lst <- list("A"=list(e1="a",e2="!"), "B"=list(e1="b", e2="#"))
# The part
# `setNames(list(.y), glue("e{length(.x) + 1}"))`
# creates a one-element list named accordingly to append to the previous list
map2(lst, seq(lst),
~ append(.x, setNames(list(.y), glue("e{length(.x) + 1}") )))
#> $A
#> $A$e1
#> [1] "a"
#>
#> $A$e2
#> [1] "!"
#>
#> $A$e3
#> [1] 1
#>
#>
#> $B
#> $B$e1
#> [1] "b"
#>
#> $B$e2
#> [1] "#"
#>
#> $B$e3
#> [1] 2
# If naming the additional element is not important, then this can simplified to
map2(lst, seq(lst), append)
# or
map2(lst, seq(lst), c)
Created on 2019-03-06 by the reprex package (v0.2.1)
Another option using Map
Map(function(x, y) c(x, "e3" = y), x = lst, y = seq_along(lst))
#$A
#$A$e1
#[1] "a"
#$A$e2
#[1] "!"
#$A$e3
#[1] 1
#$B
#$B$e1
#[1] "b"
#$B$e2
#[1] "#"
#$B$e3
#[1] 2
This could be written even more concise as
Map(c, lst, e3 = seq_along(lst))
Thanks to #thelatemail
We can use a for loop as well
for(i in seq_along(lst)) lst[[i]]$e3 <- i
Assuming I understood correctly, that you want to add a 3rd element to each nested list which contains the index of that list in it's parent list. This works:
library(rlist)
lst <- list("A"=list(e1="a",e2="!"), "B"=list(e1="b", e2="#"))
for(i in seq(1:length(lst))){
lst[[i]] <- list.append(lst[[i]],e3=i)
}
lst
We can loop along the length of lst with lapply, adding this sequential index to each element.
lst2 <- lapply(seq_along(lst), function(i) {
df <- lst[[i]]
df$e3 <- i
return(df)
})
names(lst2) <- names(lst) # Preserve names from lst
Or, if you're not scared about modifying in place:
lapply(seq_along(lst), function(i) {
lst[[i]]$e3 <<- i
})
Both give the same output:
$A
$A$e1
[1] "a"
$A$e2
[1] "!"
$A$e3
[1] 1
$B
$B$e1
[1] "b"
$B$e2
[1] "#"
$B$e3
[1] 2

Using lapply to apply function to each row in a tibble

This is my code that attempts apply a function to each row in a tibble , mytib :
> mytib
# A tibble: 3 x 1
value
<chr>
1 1
2 2
3 3
Here is my code where I'm attempting to apply a function to each line in the tibble :
mytib = as_tibble(c("1" , "2" ,"3"))
procLine <- function(f) {
print('here')
print(f)
}
lapply(mytib , procLine)
Using lapply :
> lapply(mytib , procLine)
[1] "here"
[1] "1" "2" "3"
$value
[1] "1" "2" "3"
This output suggests the function is not invoked once per line as I expect the output to be :
here
1
here
2
here
3
How to apply function to each row in tibble ?
Update : I appreciate the supplied answers that allow my expected result but what have I done incorrectly with my implementation ? lapply should apply a function to each element ?
invisible is used to avoid displaying the output. Also you have to loop through elements of the column named 'value', instead of the column as a whole.
invisible( lapply(mytib$value , procLine) )
# [1] "here"
# [1] "1"
# [1] "here"
# [1] "2"
# [1] "here"
# [1] "3"
lapply loops through columns of a data frame by default. See the example below. The values of two columns are printed as a whole in each iteration.
mydf <- data.frame(a = letters[1:3], b = 1:3, stringsAsFactors = FALSE )
invisible(lapply( mydf, print))
# [1] "a" "b" "c"
# [1] 1 2 3
To iterate through each element of a column in a data frame, you have to loop twice like below.
invisible(lapply( mydf, function(x) lapply(x, print)))
# [1] "a"
# [1] "b"
# [1] "c"
# [1] 1
# [1] 2
# [1] 3

Convert a character variable to a list of list

i want to convert a character variable to a list of list. My character looks like as follows:
"[["a",2],["b",5]]"
The expected list should contain two lists with a character and a number for each
Looks like a JSON list to me, which will make your parsing job pretty simple:
x <- '[["a",2],["b",5]]'
library(jsonlite)
fromJSON(x, simplifyVector=FALSE)
#[[1]]
#[[1]][[1]]
#[1] "a"
#
#[[1]][[2]]
#[1] 2
#
#
#[[2]]
#[[2]][[1]]
#[1] "b"
#
#[[2]][[2]]
#[1] 5
If you want it combined back to columns instead, just let the simplification occur by default:
fromJSON(x)
# [,1] [,2]
#[1,] "a" "2"
#[2,] "b" "5"
Here is one possibility via base R,
xx <- '[[a, 2], [b, 5]]'
lapply(split(matrix(gsub('[[:punct:]]', '', unlist(strsplit(xx, ','))),
nrow = 2, byrow = T), 1:2),
function(i) list(i[[1]], as.numeric(i[[2]])))
#$`1`
#$`1`[[1]]
#[1] "a"
#$`1`[[2]]
#[1] 2
#$`2`
#$`2`[[1]]
#[1] " b"
#$`2`[[2]]
#[1] 5

How to check the existence of elements of list in r

How can I check if an element of list exists or not. This is a list of lists so for example I want to check whether the third element l1[[3]] exists or not. I have tried is.null(l1[["3"]])
but it returns false no matter whether it exists or not and if I use is.null(l1[[3]]) it will give the error of subscript out of bind in case it does not exists but not TRUE.
How should I che
tl;dr:
If you want to check if element n exists, even if checking at end of a list or an empty list, use:
length(mylist) >= n # TRUE indicates exists. FALSE indicates DNE
For nested lists, make sure to check the correct list. eg:
length(outerlist[[innerlist]]) >= n
NULL in lists in R has some differences from what one is used to in other languages. For example, if we replace the element of a list by NULL, all subsequent elements are shifted over, and the list is left with a length of one less.
# SAMPLE DATA
mylist <- as.list(LETTERS[1:5])
[[1]]
[1] "A"
[[2]]
[1] "B"
[[3]]
[1] "C"
[[4]]
[1] "D"
[[5]]
[1] "E"
Testing for NULL in elements 3 & 6. Not quite the information we are looking for.
is.null(mylist[[3]])
# FALSE
is.null(mylist[[6]])
# Error in mylist[[6]] : subscript out of bounds
Instead we check the length of the list:
length(mylist) >= 3 # TRUE
length(mylist) >= 5 # TRUE
length(mylist) >= 6 # FALSE
Removing the 3rd element. Notice that the "empty slot" is not preserved. (ie, element 4, becomes element 3, etc..)
mylist[[3]] <- NULL
[[1]]
[1] "A"
[[2]]
[1] "B"
[[3]]
[1] "D"
[[4]]
[1] "E"
length(mylist) >= 3 # TRUE
length(mylist) >= 5 # FALSE
length(mylist) >= 6 # FALSE
An empty list will have length of 0
emptyList <- list()
length(emptyList) # 0
nestedList <- list( letters=list("A", "B", "C"), empty=list(), words=list("Hello", "World"))
length(nestedList)
# [1] 3
lapply(nestedList, length)
# $letters
# [1] 3
#
# $empty
# [1] 0
#
# $words
# [1] 2
Note that you can incoporate NULL into a list. Which is when testing for NULL is applicable. For example:
myListWithNull <- list("A", "B", NULL, "D")
is.null(myListWithNull[[3]])
# TRUE
length(myListWithNull) >= 3
# TRUE
As I posted here, rather than checking the length of the whole list, it's possible to check the length of the element itself to check for NULL values. As far as I can tell, all values except NULL have a length greater than 0.
x <- list(4, -1, NULL, NA, Inf, -Inf, NaN, T, x = 0, y = "", z = c(1,2,3))
lapply(x, function(el) print(length(el)))
[1] 1
[1] 1
[1] 0
[1] 1
[1] 1
[1] 1
[1] 1
[1] 1
[1] 1
[1] 1
[1] 3
Thus we could make a simple function that works with both named and numbered indices:
element.exists <- function(var, element)
{
tryCatch({
if(length(var[[element]]) > -1)
return(T)
}, error = function(e) {
return(F)
})
}
If the element doesn't exist, it causes an out-of-bounds condition caught by the tryCatch block.
As evaluation of statements in if stops as soon as a condition is false, you can use the following to reliably check if an element is empty:
if(length(l1)<n || is.null(l1[[n]]){ # TRUE only if not NULL
}
Alternatively you can use named lists
is.null(l1[["a"]])
behaves independently from the length of the list.

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