Extract {base} | R Documentation |

Operators acting on vectors, matrices, arrays and lists to extract or replace parts.

```
x[i]
x[i, j, ... , drop = TRUE]
x[[i, exact = TRUE]]
x[[i, j, ..., exact = TRUE]]
x$name
getElement(object, name)
x[i] <- value
x[i, j, ...] <- value
x[[i]] <- value
x$name <- value
```

`x, object` |
object from which to extract element(s) or in which to replace element(s). |

`i, j, ...` |
indices specifying elements to extract or replace. Indices are
For When indexing arrays by An index value of |

`name` |
A literal character string or a name (possibly backtick
quoted). For extraction, this is normally (see under
‘Environments’) partially matched to the |

`drop` |
For matrices and arrays. If |

`exact` |
Controls possible partial matching of |

`value` |
typically an array-like |

These operators are generic. You can write methods to handle indexing
of specific classes of objects, see InternalMethods as well as
`[.data.frame`

and `[.factor`

. The
descriptions here apply only to the default methods. Note that
separate methods are required for the replacement functions
`[<-`

, `[[<-`

and `$<-`

for use when indexing occurs on
the assignment side of an expression.

The most important distinction between `[`

, `[[`

and
`$`

is that the `[`

can select more than one element whereas
the other two select a single element.

The default methods work somewhat differently for atomic vectors,
matrices/arrays and for recursive (list-like, see
`is.recursive`

) objects. `$`

is only valid for
recursive objects (and `NULL`

), and is only discussed in the section below on
recursive objects.

Subsetting (except by an empty index) will drop all attributes except
`names`

, `dim`

and `dimnames`

.

Indexing can occur on the right-hand-side of an expression for
extraction, or on the left-hand-side for replacement. When an index
expression appears on the left side of an assignment (known as
*subassignment*) then that part of `x`

is set to the value
of the right hand side of the assignment. In this case no partial
matching of character indices is done, and the left-hand-side is
coerced as needed to accept the values. For vectors, the answer will
be of the higher of the types of `x`

and `value`

in the
hierarchy raw < logical < integer < double < complex < character <
list < expression. Attributes are preserved (although `names`

,
`dim`

and `dimnames`

will be adjusted suitably).
Subassignment is done sequentially, so if an index is specified more
than once the latest assigned value for an index will result.

It is an error to apply any of these operators to an object which is not subsettable (e.g., a function).

The usual form of indexing is `[`

. `[[`

can be used to
select a single element *dropping* `names`

, whereas
`[`

keeps them, e.g., in `c(abc = 123)[1]`

.

The index object `i`

can be numeric, logical, character or empty.
Indexing by factors is allowed and is equivalent to indexing by the
numeric codes (see `factor`

) and not by the character
values which are printed (for which use `[as.character(i)]`

).

An empty index selects all values: this is most often used to replace
all the entries but keep the `attributes`

.

Matrices and arrays are vectors with a dimension attribute and so all
the vector forms of indexing can be used with a single index. The
result will be an unnamed vector unless `x`

is one-dimensional
when it will be a one-dimensional array.

The most common form of indexing a `k`

-dimensional array is to
specify `k`

indices to `[`

. As for vector indexing, the
indices can be numeric, logical, character, empty or even factor.
And again, indexing by factors is equivalent to indexing by the
numeric codes, see ‘Atomic vectors’ above.

An empty index (a comma separated blank) indicates that all entries in
that dimension are selected.
The argument `drop`

applies to this form of indexing.

A third form of indexing is via a numeric matrix with the one column
for each dimension: each row of the index matrix then selects a single
element of the array, and the result is a vector. Negative indices are
not allowed in the index matrix. `NA`

and zero values are allowed:
rows of an index matrix containing a zero are ignored, whereas rows
containing an `NA`

produce an `NA`

in the result.

Indexing via a character matrix with one column per dimensions is also
supported if the array has dimension names. As with numeric matrix
indexing, each row of the index matrix selects a single element of the
array. Indices are matched against the appropriate dimension names.
`NA`

is allowed and will produce an `NA`

in the result.
Unmatched indices as well as the empty string (`""`

) are not
allowed and will result in an error.

A vector obtained by matrix indexing will be unnamed unless `x`

is one-dimensional when the row names (if any) will be indexed to
provide names for the result.

Indexing by `[`

is similar to atomic vectors and selects a list
of the specified element(s).

Both `[[`

and `$`

select a single element of the list. The
main difference is that `$`

does not allow computed indices,
whereas `[[`

does. `x$name`

is equivalent to
`x[["name", exact = FALSE]]`

. Also, the partial matching
behavior of `[[`

can be controlled using the `exact`

argument.

`getElement(x, name)`

is a version of `x[[name, exact = TRUE]]`

which for formally classed (S4) objects returns `slot(x, name)`

,
hence providing access to even more general list-like objects.

`[`

and `[[`

are sometimes applied to other recursive
objects such as calls and expressions. Pairlists (such
as calls) are coerced to lists for extraction by `[`

, but all
three operators can be used for replacement.

`[[`

can be applied recursively to lists, so that if the single
index `i`

is a vector of length `p`

, `alist[[i]]`

is
equivalent to `alist[[i1]]...[[ip]]`

providing all but the
final indexing results in a list.

Note that in all three kinds of replacement, a value of `NULL`

deletes the corresponding item of the list. To set entries to
`NULL`

, you need `x[i] <- list(NULL)`

.

When `$<-`

is applied to a `NULL`

`x`

, it first coerces
`x`

to `list()`

. This is what also happens with `[[<-`

where in **R** versions less than 4.y.z, a length one value resulted in a
length one (atomic) *vector*.

Both `$`

and `[[`

can be applied to environments. Only
character indices are allowed and no partial matching is done. The
semantics of these operations are those of ```
get(i, env = x,
inherits = FALSE)
```

. If no match is found then `NULL`

is
returned. The replacement versions, `$<-`

and `[[<-`

, can
also be used. Again, only character arguments are allowed. The
semantics in this case are those of ```
assign(i, value, env = x,
inherits = FALSE)
```

. Such an assignment will either create a new
binding or change the existing binding in `x`

.

When extracting, a numerical, logical or character `NA`

index picks
an unknown element and so returns `NA`

in the corresponding
element of a logical, integer, numeric, complex or character result,
and `NULL`

for a list. (It returns `00`

for a raw result.)

When replacing (that is using indexing on the lhs of an
assignment) `NA`

does not select any element to be replaced. As
there is ambiguity as to whether an element of the rhs should
be used or not, this is only allowed if the rhs value is of length one
(so the two interpretations would have the same outcome).
(The documented behaviour of S was that an `NA`

replacement index
‘goes nowhere’ but uses up an element of `value`

:
Becker *et al* p. 359. However, that has not been true of
other implementations.)

Note that these operations do not match their index arguments in the
standard way: argument names are ignored and positional matching only is
used. So `m[j = 2, i = 1]`

is equivalent to `m[2, 1]`

and
**not** to `m[1, 2]`

.

This may not be true for methods defined for them; for example it is
not true for the `data.frame`

methods described in
`[.data.frame`

which warn if `i`

or `j`

is named and have undocumented behaviour in that case.

To avoid confusion, do not name index arguments (but `drop`

and
`exact`

must be named).

These operators are also implicit S4 generics, but as primitives, S4
methods will be dispatched only on S4 objects `x`

.

The implicit generics for the `$`

and `$<-`

operators do not
have `name`

in their signature because the grammar only allows
symbols or string constants for the `name`

argument.

Character indices can in some circumstances be partially matched (see
`pmatch`

) to the names or dimnames of the object being
subsetted (but never for subassignment). Unlike S (Becker *et
al* p. 358), **R** never uses partial matching when extracting by
`[`

, and partial matching is not by default used by `[[`

(see argument `exact`

).

Thus the default behaviour is to use partial matching only when
extracting from recursive objects (except environments) by `$`

.
Even in that case, warnings can be switched on by
`options(warnPartialMatchDollar = TRUE)`

.

Neither empty (`""`

) nor `NA`

indices match any names, not
even empty nor missing names. If any object has no names or
appropriate dimnames, they are taken as all `""`

and so match
nothing.

Attempting to apply a subsetting operation to objects for which this is
not possible signals an error of class
`notSubsettableError`

. The `object`

component of the error
condition contains the non-subsettable object.

Subscript out of bounds errors are signaled as errors of class
`subscriptOutOfBoundsError`

. The `object`

component of the
error condition contains the object being subsetted. The integer
`subscript`

component is zero for vector subscripting, and for
multiple subscripts indicates which subscript was out of bounds. The
`index`

component contains the erroneous index.

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
*The New S Language*.
Wadsworth & Brooks/Cole.

`names`

for details of matching to names, and
`pmatch`

for partial matching.

`[.data.frame`

and `[.factor`

for the
behaviour when applied to data.frame and factors.

`Syntax`

for operator precedence, and the
‘R Language Definition’ manual about indexing details.

`NULL`

for details of indexing null objects.

```
x <- 1:12
m <- matrix(1:6, nrow = 2, dimnames = list(c("a", "b"), LETTERS[1:3]))
li <- list(pi = pi, e = exp(1))
x[10] # the tenth element of x
x <- x[-1] # delete the 1st element of x
m[1,] # the first row of matrix m
m[1, , drop = FALSE] # is a 1-row matrix
m[,c(TRUE,FALSE,TRUE)]# logical indexing
m[cbind(c(1,2,1),3:1)]# matrix numeric index
ci <- cbind(c("a", "b", "a"), c("A", "C", "B"))
m[ci] # matrix character index
m <- m[,-1] # delete the first column of m
li[[1]] # the first element of list li
y <- list(1, 2, a = 4, 5)
y[c(3, 4)] # a list containing elements 3 and 4 of y
y$a # the element of y named a
## non-integer indices are truncated:
(i <- 3.999999999) # "4" is printed
(1:5)[i] # 3
## named atomic vectors, compare "[" and "[[" :
nx <- c(Abc = 123, pi = pi)
nx[1] ; nx["pi"] # keeps names, whereas "[[" does not:
nx[[1]] ; nx[["pi"]]
## recursive indexing into lists
z <- list(a = list(b = 9, c = "hello"), d = 1:5)
unlist(z)
z[[c(1, 2)]]
z[[c(1, 2, 1)]] # both "hello"
z[[c("a", "b")]] <- "new"
unlist(z)
## check $ and [[ for environments
e1 <- new.env()
e1$a <- 10
e1[["a"]]
e1[["b"]] <- 20
e1$b
ls(e1)
## partial matching - possibly with warning :
stopifnot(identical(li$p, pi))
op <- options(warnPartialMatchDollar = TRUE)
stopifnot( identical(li$p, pi), #-- a warning
inherits(tryCatch (li$p, warning = identity), "warning"))
## revert the warning option:
if(is.null(op[[1]])) op[[1]] <- FALSE; options(op)
```

[Package *base* version 4.2.0 Index]