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NA {base}

‘Not Available’ / Missing Values
R 3.0.2


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 indicates which elements are missing.

The generic function<- sets elements to NA.


## S3 replacement method for class 'data.frame': <- value)


an R object to be tested: the default method handles atomic vectors, lists and pairlists.
a suitable index vector for use with x.


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<-. 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<- 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 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 methods also works for lists and pairlists:
For, elementwise the result is false unless that element is a length-one atomic vector and the single element of that vector is regarded as NA or NaN (note that any methods for the class of the atomic vector is ignored).

The data frame method for 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.

See Also

NaN, is.nan, etc., and the utility function complete.cases.

na.action, na.omit, on how methods can be tuned to deal with missing values.

Examples, NA))        #> FALSE  TRUE, NA))) #> FALSE FALSE
(xx <- c(0:4)) <- c(2, 4)
xx                     #> 0 NA  2 NA  4

Documentation reproduced from R 3.0.2. License: GPL-2.