# [Rcpp-devel] Missing values

Thu Nov 15 23:36:30 CET 2012

```Hi all,

I'm working on a description of how missing values work in Rcpp
(expanding on FAQ 3.4).  I'd really appreciate any comments,
corrections or suggestions on the text below.

Thanks!

# Missing values

If you're working with missing values, you need to know two things:

* what happens when you put missing values in scalars (e.g. `double`)
* how to get and set missing values in vectors (e.g. `NumericVector`)

## Scalars

The following code explores what happens when you coerce the first
element of a vector into the corresponding scalar:

cppFunction('int first_int(IntegerVector x) {
return(x);
}')
cppFunction('double first_num(NumericVector x) {
return(x);
}')
cppFunction('std::string first_char(CharacterVector x) {
return((std::string) x);
}')
cppFunction('bool first_log(LogicalVector x) {
return(x);
}')

first_log(NA)
first_int(NA_integer_)
first_num(NA_real_)
first_char(NA_character_)

So

* `NumericVector` -> `double`: NAN

* `IntegerVector` -> `int`: NAN (not sure how this works given that
integer types don't usually have a missing value)

* `CharacterVector` -> `std::string`: the string "NA"

* `LogicalVector` -> `bool`: TRUE

If you're working with doubles, depending on your problem, you may be
able to get away with ignoring missing values and working with NaNs.
R's missing values are a special type of the IEEE 754 floating point
number NaN (not a number). That means if you coerce them to `double`
or `int` in your C++ code, they will behave like regular NaN's.

In a logical context they always evaluate to FALSE:

evalCpp("NAN == 1")
evalCpp("NAN < 1")
evalCpp("NAN > 1")
evalCpp("NAN == NAN")

But be careful when combining then with boolean values:

evalCpp("NAN && TRUE")
evalCpp("NAN || FALSE")

In numeric contexts, they propagate similarly to NA in R:

evalCpp("NAN + 1")
evalCpp("NAN - 1")
evalCpp("NAN / 1")
evalCpp("NAN * 1")

## Vectors

To set a missing value in a vector, you need to use a missing value
specific to the type of vector. Unfortunately these are not named
terribly consistently:

cppFunction('
List missing_sampler() {

NumericVector num(1);
num = NA_REAL;

IntegerVector intv(1);
intv = NA_INTEGER;

LogicalVector lgl(1);
lgl = NA_LOGICAL;

CharacterVector chr(1);
chr = NA_STRING;

List out(4);
out = num;
out = intv;
out = lgl;
out = chr;
return(out);
}
')
str(missing_sampler())

To check if a value in a vector is missing, use `ISNA`:

cppFunction('
LogicalVector is_na2(NumericVector x) {
LogicalVector out(x.size());

NumericVector::iterator x_it;
LogicalVector::iterator out_it;
for (x_it = x.begin(), out_it = out.begin(); x_it != x.end();
x_it++, out_it++) {
*out_it = ISNA(*x_it);
}
return(out);
}
')
is_na2(c(NA, 5.4, 3.2, NA))

Rcpp provides a helper function called `is_na` that works similarly to
`is_na2` above, producing a logical vector that's true where the value
in the vector was missing.

--
RStudio / Rice University