When subsetting rows with a factor with equal (==), NA's are also included. It doesn't happen with %in%. Is it normal?
equals, na, r, subset
Solution
Yes, the return types of `==` and `%in%` are different with respect to `NA` because of how `"%in%"` is defined...
# Data...
x <- c("A",NA,"A")
# When NA is encountered NA is returned
# Philosophically correct - who knows if the
# missing value at NA is equal to "A"?!
x=="A"
#[1] TRUE NA TRUE
x[x=="A"]
#[1] "A" NA "A"
# When NA is encountered by %in%, FALSE is returned, rather than NA
x %in% "A"
#[1] TRUE FALSE TRUE
x[ x %in% "A" ]
#[1] "A" "A"
This is because (from the docs)...
`%in%` is an alias for `match`, which is defined as
"%in%" <- function(x, table) match(x, table, nomatch = 0) > 0
If we redefine it to the standard definition of `match` you will see that it behaves in the same way as `==`
"%in2%" <- function(x,table) match(x, table, nomatch = NA_integer_) > 0
x %in2% "A"
#[1] TRUE NA TRUE
Problem
Suppose I have a factor A with 3 levels A1, A2, A3 and with NA's. Each appears in 10 cases, so there is a total of 40 cases. If I do ``` subset1 <- df[df$A=="A1",] dim(subset1) # 20, i.e., 10 for A1 and 10 for NA's summary(subset1$A) # both A1 and NA have non-zero counts subset2 <- df[df$A %in% c("A1"),] dim(subset2) # 10, as expected summary(subset2$A) # only A1 has non-zero count ``` And it is the same whether the class of the variable used for subsetting is factor or integer. Is it just how equal (and >, <) works? So should I just stick to `%in%` for factors and always include `!is.na` when using equal? Thanks!