问题
I have the following data.frame:
x <- data.frame(A = c("Y", "Y", "Z", NA),
B = c(NA, TRUE, FALSE, TRUE),
C = c(TRUE, TRUE, NA, FALSE))
And I need to compute the following table with xtabs
:
A B C
Y 1 2
Z 0 0
<NA> 1 0
I was told to use na.action = NULL, which indeed returns the table I need:
xtabs(formula = cbind(B, C) ~ A,
data = x,
addNA = TRUE,
na.action = NULL)
A B C
Y 1 2
Z 0 0
<NA> 1 0
However, na.action = na.pass
returns a different table:
xtabs(formula = cbind(B, C) ~ A,
data = x,
addNA = TRUE,
na.action = na.pass)
A B C
Y 2
Z 0
<NA> 1 0
But the documentation of xtabs
says:
na.action
When it is na.pass and formula has a left hand side (with counts), sum(*, na.rm = TRUE) is used instead of sum(*) for the counts.
With aggregate
, na.action = na.pass
returns the expected result (and also na.action = NULL
):
aggregate(formula = cbind(B, C) ~ addNA(A),
data = x,
FUN = sum,
na.rm = TRUE,
na.action = na.pass) # same result with na.action = NULL
addNA(A) B C
1 Y 1 2
2 Z 0 0
3 <NA> 1 0
Although I get the table I need with xtabs
, I do not understand the behavior of na.action
in xtabs
from the documentation. So my questions are:
- Is the behavior of
na.action
inxtabs
consistent with the documentation? Unless I am missing something,na.action = na.pass
does not result insum(*, na.rm = TRUE)
. - Is
na.action = NULL
documented somewhere? - In
xtabs
source code there isna.rm <- identical(naAct, quote(na.omit)) || identical(naAct, na.omit) || identical(naAct, "na.omit")
. But I saw nothing forna.action = na.pass
andna.action = NULL
. How dona.action = na.pass
andna.action = NULL
work?
回答1:
It's difficult to give a cannonical answer without describing how xtabs
works. If we step through the main points of its source code, we'll see clearly what's going on.
After some basic type checking, the call to xtabs
works internally by first creating a data frame of all the variables contained in your formula using stats::model.frame
, and it is to this that the na.action
parameter is passed.
The way it does this is quite clever. xtabs
first copies the call you made to it via match.call
, like this:
m <- match.call(expand.dots = FALSE)
Then it strips out the parameters that don't need passed to stats::model.frame
like this:
m$... <- m$exclude <- m$drop.unused.levels <- m$sparse <- m$addNA <- NULL
As promised in the help file, if addNA
is TRUE
and na.action
is missing, it will now default to na.pass
:
if (addNA && missing(na.action))
m$na.action <- quote(na.pass)
Then it changes the function to be called from xtabs
to stats::model.frame
like this:
m[[1L]] <- quote(stats::model.frame)
So the object m
is a call (and is also a standalone reprex), which in your case looks like this:
stats::model.frame(formula = cbind(B, C) ~ A, data = list(A = structure(c(1L,
1L, 2L, NA), .Label = c("Y", "Z"), class = "factor"), B = c(NA, TRUE, FALSE, TRUE),
C = c(TRUE, TRUE, NA, FALSE)), na.action = NULL)
Note that your na.action = NULL
has been passed to this call. This has the effect of keeping all NA
values in the frame. When the above call is evaluated, it gives this data frame:
eval(m)
#> cbind(B, C).B cbind(B, C).C A
#> 1 NA TRUE Y
#> 2 TRUE TRUE Y
#> 3 FALSE NA Z
#> 4 TRUE FALSE <NA>
Note that this is the same result you would get if you passed na.action = na.pass
:
stats::model.frame(formula = cbind(B, C) ~ A, data = list(A = structure(c(1L,
1L, 2L, NA), .Label = c("Y", "Z"), class = "factor"), B = c(NA, TRUE, FALSE, TRUE),
C = c(TRUE, TRUE, NA, FALSE)), na.action = na.pass)
#> cbind(B, C).B cbind(B, C).C A
#> 1 NA TRUE Y
#> 2 TRUE TRUE Y
#> 3 FALSE NA Z
#> 4 TRUE FALSE <NA>
However, if you passed na.action = na.omit
, you would only be left with a single row, since only row 2 has no NA
values.
In any case, the "model frame" result is stored in the variable mf
. This is then split into the independent variable(s), - in your case, column A, and the response variable - in your case cbind(B, C)
.
The response is stored in y
and the variable in by
:
i <- attr(attr(mf, "terms"), "response")
by <- mf[-i]
y <- mf[[i]]
Now, by
is processed to ensure each independent variable is a factor, and that any NA
values are converted into factor levels if you have specified addNA = TRUE
:
by <- lapply(by, function(u) {
if (!is.factor(u))
u <- factor(u, exclude = exclude)
else if (has.exclude)
u <- factor(as.character(u), levels = setdiff(levels(u),
exclude), exclude = NULL)
if (addNA)
u <- addNA(u, ifany = TRUE)
u[, drop = drop.unused.levels]
})
Now we come to the crux. The na.action
is used again to determine how the NA
values in the response variable will be counted. In your case, since you passed na.action = NULL
, you will see that naAct
will get the value stored in getOption("na.action")
, which if you have never changed it, should be set to na.omit
. This in turn will cause the value of the variable na.rm,
to be TRUE
:
naAct <- if (!is.null(m$na.action)) {
m$na.action
}else {getOption("na.action", default = quote(na.omit))}
na.rm <- identical(naAct, quote(na.omit)) || identical(naAct,
na.omit) || identical(naAct, "na.omit")
Note that if you had passed na.action = na.pass
, then na.rm
would be FALSE
if you trace this piece of code.
Finally, we come to the section where your xtabs
table is built using sum
inside a tapply
, which is itself inside an lapply
.
lapply(as.data.frame(y), tapply, by, sum, na.rm = na.rm, default = 0L)
You can see that the na.rm
variable is used to determine whether to remove NA
s from the columns before attempting to sum them. The result of this lapply
is then coerced into the final cross tab.
So how does this answer your question?
It is true when the documentation says that if you don't pass an na.action
, it will default to na.pass
. However, the na.action
is used in two places: once in the call to model.frame
and once to determine the value of na.rm
. It is very clear from the source code that if na.action
is na.pass
, then na.rm
will be FALSE
, so you will miss out on the counts of any response groups containing NA
values. This is the opposite of what is written in the help file.
The only way round this is to pass na.action = NULL
, since this will allow model.frame
to keep NA
values, but will also cause the sum
function to default to na.rm
.
TL;DR The documentation for xtabs
is wrong on this point.
回答2:
I'm sorry I'm only joining now. Indeed, the last half dozen changes to xtabs() were all by me, so I have to take responsibility here, too.
Delving into all variants and ramifications of xtabs()
always takes some time which I've not taken yet (this time; of course did back then..).
But you finally deserve an answer:
Yes, there's bug -- either in the R code or in the documentation (and that "or" is inclusive .. ;-)
my current gut feeling is pointing to a bug in the help (file) rather than the implementation
R's bugzilla is the place we should get into details about this, not the least because that's "wired" to the R Core team's channels.
--> follow up there: https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17770.
来源:https://stackoverflow.com/questions/61240049/inconsistency-of-na-action-between-xtabs-and-aggregate-in-r