R Programming Questions and Answers – Loop Functions – 2

This set of R Programming online quiz focuses on “Loop Functions – 2”.

1. What will be the output of the following R code?

> x <- list(a = 1:4, b = rnorm(10), c = rnorm(20, 1), d = rnorm(100, 5))
> lapply(x, mean)

a)

$a
[1] 2.5
$b
[1] 1.248845
$c
[1] 1.9935285
Loop Functions 90
$d
[1] 5.051388

b)

$a
[1] 2.5
$b
[1] 0.248845
$c
[1] 0.9935285
Loop Functions 90
$d
[1] 5.051388

c)

$a
[1] 3.5
$b
[1] 0.248845
$c
[1] 0.9935285
Loop Functions 90
$d
[1] 5.051388

d) Error
View Answer

2. Point out the wrong statement?
a) The sapply() function behaves similarly to lapply()
b) With multiple factors and many levels, creating an interaction can result in many levels that are empty
c) apply() can be thought of as a combination of split() and sapply() for vectors only
d) You can use tsplit() to evaluate a function single time each with a same argument
View Answer

3. What will be the output of the following R code?

> x <- 1:4
> lapply(x, runif)

a)

[[1]]
[1] 0.02778712
[[2]]
[1] 0.5273108 0.8803191
[[3]]
[1] 0.37306337 0.04795913 0.13862825
[[4]]
[1] 0.3214921 0.1548316 0.1322282 0.2213059

b)

[[1]]
[1] 1.02778712
[[2]]
[1] 2.5273108 0.8803191
[[3]]
[1] 3.37306337 0.04795913 0.13862825
[[4]]
[1] 0.3214921 0.1548316 0.1322282 0.2213059

c)

[[1]]
[1] 1.02778712
[[2]]
[1] 0.5273108 0.8803191
[[3]]
[1] 0.37306337 0.04795913 0.13862825
[[4]]
[1] 3.3214921 2.1548316 1.1322282 0.2213059

d) Error
View Answer

4. Which of the following R code will print the following result?

[[1]]
[1] 2.263808
[[2]]
[1] 1.314165 9.815635
[[3]]
[1] 3.270137 5.069395 6.814425
[[4]]
[1] 0.9916910 1.1890256 0.5043966 9.2925392

a)

> x <- 1:4
> lapply(x, runif, min = 0, max = 10)

b)

> x <- 1:4
> lapply(x, runif, min = 0, max = 9)

c)

> x <- 1:3
> lapply(x, runif, min = 0, max = 10)

d)

> x <- 1:4
> lapply(x, runif, min = 0, max = 6)

5. Point out the correct statement?
a) split() takes elements of the list and passes them as the first argument of the function you are applying
b) You can use tsplit() to evaluate a function single time each with a same argument
c) Sequence of operations is sometimes referred to as “map-reduce”
d) apply() can be thought of as a combination of split() and sapply() for vectors only
View Answer

6. What will be the output of the following R code?

> x <- list(a = matrix(1:4, 2, 2), b = matrix(1:6, 3, 2))
> lapply(x, function(elt) { elt[,1] })

a)

$a
[1] 1 2
$b
[1] 1 2 3

b)

$a
[1] 1 2 3
$b
[1] 1 2 3

c)

$a
[1] 1 2 3
$b
[1] 1 2

d) Error
View Answer

7. The _____ function takes a vector or other objects and splits it into groups determined by a factor or list of factors.
a) apply()
b) lsplit()
c) split()
d) mapply()
View Answer

8. Which of the following is valid body of split function?
a) function (x, f)
b) function (x, drop = FALSE, …)
c) function (x, f, drop = FALSE, …)
d) function (drop = FALSE, …)
View Answer

9. What will be the output of the following R code?

> f <- function(elt) {
+ elt[, 1]
+ }
> lapply(x, f)

a)

$a
[1] 1 2
$b
[1] 1 2 3

b)

$a
[1] 1 2 3
$b
[1] 1 2 3

c)

$a
[1] 1 2 3
$b
[1] 1 2

d) Error
View Answer

10. What will be the output of the following R code?

> x <- list(a = 1:4, b = rnorm(10), c = rnorm(20, 1), d = rnorm(100, 5))
> sapply(x, mean)

a)

a b c d
2.500000 -0.251483 1.481246 4.968715

b)

a b c d
2.500000 -3.251483 2.481246 5.968715

c)

a b c d
3.500000 0.251483 1.481246 4.968715

d) Error
View Answer

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