Usage Arguments Details Value References See Also Examples
1 | x %notin% table
|
x |
vector or |
table |
vector or |
%in%
is currently defined as
"%in%" <- function(x, table) match(x, table, nomatch = 0) > 0
Factors, raw vectors and lists are converted to character vectors, and
then x
and table
are coerced to a common type (the later
of the two types in R's ordering, logical < integer < numeric <
complex < character) before matching. If incomparables
has
positive length it is coerced to the common type.
Matching for lists is potentially very slow and best avoided except in simple cases.
Exactly what matches what is to some extent a matter of definition.
For all types, NA
matches NA
and no other value.
For real and complex values, NaN
values are regarded
as matching any other NaN
value, but not matching NA
,
where for complex x
, real and imaginary parts must match both
(unless containing at least one NA
).
Character strings will be compared as byte sequences if any input is
marked as "bytes"
, and otherwise are regarded as equal if they are
in different encodings but would agree when translated to UTF-8 (see
Encoding
).
That %in%
never returns NA
makes it particularly
useful in if
conditions.
A vector of the same length as x
.
match
: An integer vector giving the position in table
of
the first match if there is a match, otherwise nomatch
.
If x[i]
is found to equal table[j]
then the value
returned in the i
-th position of the return value is j
,
for the smallest possible j
. If no match is found, the value
is nomatch
.
%in%
: A logical vector, indicating if a match was located for
each element of x
: thus the values are TRUE
or
FALSE
and never NA
.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
pmatch
and charmatch
for (partial)
string matching, match.arg
, etc for function argument
matching.
findInterval
similarly returns a vector of positions, but
finds numbers within intervals, rather than exact matches.
is.element
for an S-compatible equivalent of %in%
.
unique
(and duplicated
) are using the same
definitions of “match” or “equality” as match()
,
and these are less strict than ==
, e.g., for
NA
and NaN
in numeric or complex vectors,
or for strings with different encodings, see also above.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ## The intersection of two sets can be defined via match():
## Simple version:
## intersect <- function(x, y) y[match(x, y, nomatch = 0)]
intersect # the R function in base is slightly more careful
intersect(1:10, 7:20)
1:10 %in% c(1,3,5,9)
sstr <- c("c","ab","B","bba","c",NA,"@","bla","a","Ba","%")
sstr[sstr %in% c(letters, LETTERS)]
"%w/o%" <- function(x, y) x[!x %in% y] #-- x without y
(1:10) %w/o% c(3,7,12)
## Note that setdiff() is very similar and typically makes more sense:
c(1:6,7:2) %w/o% c(3,7,12) # -> keeps duplicates
setdiff(c(1:6,7:2), c(3,7,12)) # -> unique values
## Illuminating example about NA matching
r <- c(1, NA, NaN)
zN <- c(complex(real = NA , imaginary = r ), complex(real = r , imaginary = NA ),
complex(real = r , imaginary = NaN), complex(real = NaN, imaginary = r ))
zM <- cbind(Re=Re(zN), Im=Im(zN), match = match(zN, zN))
rownames(zM) <- format(zN)
zM ##--> many "NA's" (= 1) and the four non-NA's (3 different ones, at 7,9,10)
length(zN) # 12
unique(zN) # the "NA" and the 3 different non-NA NaN's
stopifnot(identical(unique(zN), zN[c(1, 7,9,10)]))
## very strict equality would have 4 duplicates (of 12):
symnum(outer(zN, zN, Vectorize(identical,c("x","y")),
FALSE,FALSE,FALSE,FALSE))
## removing "(very strictly) duplicates",
i <- c(5,8,11,12) # we get 8 pairwise non-identicals :
Ixy <- outer(zN[-i], zN[-i], Vectorize(identical,c("x","y")),
FALSE,FALSE,FALSE,FALSE)
stopifnot(identical(Ixy, diag(8) == 1))
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