| NA {base} | R Documentation |
NA is a logical constant of length 1 which contains a missing
value indicator. NA can be coerced to any other vector
type except raw. There are also constants NA_integer_,
NA_real_, NA_complex_ and NA_character_ of the
other atomic vector types which support missing values: all of these
are reserved words in the R language.
The generic function is.na indicates which elements are missing.
The generic function is.na<- sets elements to NA.
NA is.na(x) ## S3 method for class 'data.frame' is.na(x) is.na(x) <- value
x |
an R object to be tested: the default method handles atomic vectors, lists and pairlists. |
value |
a suitable index vector for use with |
The NA of character type is distinct from the
string "NA". Programmers who need to specify an explicit
string NA should use NA_character_ rather than
"NA", or set elements to NA using is.na<-.
is.na(x) works elementwise when x is a
list. It is generic: you can write methods to handle
specific classes of objects, see InternalMethods. A complex
value is regarded as NA if either its real or imaginary part is
NA or NaN.
Function is.na<- may provide a safer way to set missingness.
It behaves differently for factors, for example.
Computations using NA will normally result in NA: a
possible exception is where NaN is also involved, in
which case either might result.
The default method for is.na applied to an atomic vector
returns a logical vector of the same length as its argument x,
containing TRUE for those elements marked NA or, for
numeric or complex vectors, NaN (!) and FALSE
otherwise. dim, dimnames and names attributes
are preserved.
The default method also works for lists and pairlists: the result for an
element is false unless that element is a length-one atomic vector and
the single element of that vector is regarded as NA or NaN.
The method is.na.data.frame returns a logical matrix with the
same dimensions as the data frame, and with dimnames taken from the
row and column names of the data frame.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
Chambers, J. M. (1998) Programming with Data. A Guide to the S Language. Springer.
NaN, is.nan, etc.,
and the utility function complete.cases.
na.action, na.omit, na.fail
on how methods can be tuned to deal with missing values.
is.na(c(1, NA)) #> FALSE TRUE is.na(paste(c(1, NA))) #> FALSE FALSE (xx <- c(0:4)) is.na(xx) <- c(2, 4) xx #> 0 NA 2 NA 4