Data selection and manipulation

Question 1

which.max(x)

Answer 1

returns the index of the greatest element of x

Question 2

which.min(x)

Answer 2

returns the index of the smallest element of x

Question 3

rev(x)

Answer 3

reverses the elements of x

Question 4

sort(x)

Answer 4

sorts the elements of x in increasing order; to sort in decreasing
order: rev(sort(x))

Question 5

cut(x,breaks)

Answer 5

divides x into intervals (factors); breaks is the number

of cut intervals or a vector of cut points

Question 6

match(x, y)

Answer 6

returns a vector of the same length than x with the elements

of x which are in y (NA otherwise)

Question 7

which(x == a)

Answer 7

returns a vector of the indices of x if the comparison op-
eration is true (TRUE), in this example the values of i for which x[i] == a (the argument of this function must be a variable of mode logi- cal)

Question 8

choose(n, k)

Answer 8

computes the combinations of k events among n repetitions = n!/[(n − k)!k!]

Question 9

na.omit(x)

Answer 9

suppresses the observations with missing data (NA) (sup- presses the corresponding line if x is a matrix or a data frame)

Question 10

na.fail(x)

Answer 10

returns an error message if x contains at least one NA

Question 11

unique(x)

Answer 11

if x is a vector or a data frame, returns a similar object but with the duplicate elements suppressed

Question 12

table(x)

Answer 12

returns a table with the numbers of the differents values of x (typically for integers or factors)

Question 13

subset(x, …)

Answer 13

returns a selection of x with respect to criteria (…, typically comparisons: x$V1 < 10); if x is a data frame, the option select gives the variables to be kept or dropped using a minus sign

Question 14

sample(x, size)

Answer 14

resample randomly and without replacement size ele- ments in the vector x, the option replace = TRUE allows to resample with replacement

Question 15

prop.table(x,margin=)

Answer 15

table entries as fraction of marginal table

Question 16

with(data, expr, …)

Answer 16

Evaluate an R expression in an environment constructed from data, possibly modifying the original data.