Lists in R

Lists

A list is an R structure that may contain object of any other types, including other lists. Lots of the modeling functions (like t.test() for the t test or lm() for linear models) produce lists as their return values, but you can also construct one yourself:

mylist <- list (a = 1:5, b = "Hi There", c = function(x) x * sin(x))

Now the list "mylist" contains three things, named "a," "b," and "c." Their lengths are different: a has length 5, b has length 1, and c is a function, so it doesn't really have a length. (Technically, it has length 1, just because somebody decided that the "length" of a function should be one.) To extract an item from a list, you can use the single brackets, but that will give you back a list. Thus

mylist[1]
$a:
[1] 1 2 3 4 5

> mylist[1] + 1      # Can we do math on that?
Error in mylist[1] + 1: Non-numeric first operand
Dumped

We can't do math on a list. Generally you will want single brackets when you're extracting pieces of a list to make into another list.

If we want one of the items in its original form, we can extract it with double square brackets, or by using the dollar sign and the name. (The items in the list don't need to have names, but in this case they do have names, since we supplied them at the time we created the list.)

mylist[[1]]
[1] 1 2 3 4 5

> mylist$a
[1] 1 2 3 4 5

> mylist$a + 1      # Can we do math on that?
[1] 2 3 4 5 6       # Answer: yes.

> mylist$a[2]       # What's the second element of the item named "a"?
[1] 2               # Answer: 2.

> mylist$a[-2]      # Give me everything from "a" except the second element
[1] 1 3 4 5         # Remember the negative subscript?

Usually a list will consist of vectors. As always, every element of a vector must be of the same type (numeric, character, logical, complex...). A list is a natural way, then, to store items of different types and lengths. For example, when you fit a statistical model you might get back a vector of (numeric) coefficients, a logical vector saying which terms were included in the model, a matrix of data, a vector of messages from the fitting routines, a so on. A list is the natural way to represent this sort of thing in R.

Adding items to, and deleting items from, a list

One useful thing about lists is how easily items can be added or deleted. To delete an item from a list, assign NULL to that item's name or number. Furthermore you can add a new element to the list simply by assigning something to a new name. (These will be added at the end of the list.) For example:

> mylist                     # Here's what mylist looks like right now
$a:
[1] 1 2 3 4 5

$b:
[1] "Hi There"

$c:
function(x)
x * sin(x)

> mylist$d <- "New item"     # Add a new item and print out the list
> mylist                     # We could have assigned to mylist[[4]]; then that
$a:                          # new element would not have had a name
[1] 1 2 3 4 5

$b:
[1] "Hi There"

$c:
function(x)
x * sin(x)

$d:
[1] "New item"

> length(mylist)             # The length of a list is the number of elements
[1] 4                        # (So for a data frame, the length is
                             # the number of columns)

> mylist$b <- NULL           # Delete item b and print out the list
> mylist
$a:
[1] 1 2 3 4 5

$c:
function(x)
x * sin(x)

$d:
[1] "New item"

Functions that act on elements of lists

This is an important topic that gets its own document. See The Apply Family of Functions.

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