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In R, a numeric variable is either a number (like 0, 42, or -3.14), or one of 4 special values: NA
, NaN
, Inf
or -Inf
. It can be hard to remember how the is.x
functions treat each of the special values, especially NA
and NaN
! The table below summarizes how each of these values is treated by different base R functions. Functions are listed in alphabetical order.
Function | Typical number | NA | NaN | Inf | -Inf |
---|---|---|---|---|---|
is.double | TRUE | FALSE | TRUE | TRUE | TRUE |
is.finite | TRUE | FALSE | FALSE | FALSE | FALSE |
is.infinite | FALSE | FALSE | FALSE | TRUE | TRUE |
is.integer | *1 | FALSE | FALSE | FALSE | FALSE |
is.na | FALSE | TRUE | TRUE | FALSE | FALSE |
is.nan | FALSE | FALSE | TRUE | FALSE | FALSE |
is.null | FALSE | FALSE | FALSE | FALSE | FALSE |
is.numeric | TRUE | *2 | TRUE | TRUE | TRUE |
*1: is.integer
can return TRUE
or FALSE
, depending on whether the number is an integer or not.
*2: R actually has different types of NA
s (see here for more details). is.numeric(NA)
returns FALSE
, but is.numeric(NA_integer_)
and is.numeric(NA_real_)
return TRUE
. Interestingly, is.numeric(NA_complex_)
returns FALSE
.
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