Thanks all for the enlightenment.
So, it does make sense that mean() produces NaN and median()/sd() NA,
from a calculation point of view at least.
But I still think it also makes sense that the mean of NA is NA as well,
be it only for consistency with other functions. That's just my opinion
of course. I can still convert NaN to NA at the end if I need to.
Best,
Ivan
--
Dr. Ivan Calandra
TraCEr, laboratory for Traceology and Controlled Experiments
MONREPOS Archaeological Research Centre and
Museum for Human Behavioural Evolution
Schloss Monrepos
56567 Neuwied, Germany
+49 (0) 2631 9772-243
https://www.researchgate.net/profile/Ivan_Calandra
On 22/08/2018 18:41, Ted Harding wrote:
I think that one can usefully look at this question from the
point of view of what "NaN" and "NA" are abbreviations for
(at any rate, according to the understanding I have adopted
since many years -- maybe over-simplified).
NaN: Mot a Number
NA: Not Available
So NA is typically used for missing values, whereas NaN
represents the reults of numerical calculations which
cannot give a result which is a definite number,
Hence 0/0 is not a number, so NaN; similarly Inf/Inf.
Thus, with your x <- c(NA, NA, NA) mean(x, na.rm=TRUE)
sum(x, na.rm=TRUE) = 0, since the set of values of x
with na.rm=TRUE is empty so the number of elements
in x is 0; hence mean = 0/0 = NaN.
But for median(x, na.rm=TRUE), because there are no available
elements in x with na.rm=TRUE, and the median is found by
searching among available elements for the value which
divides the set of values into two halves, the median
is not available, hence NA.
Best wishes to all,
Ted.
On Wed, 2018-08-22 at 11:24 -0400, Marc Schwartz via R-help wrote:
Hi,
It might even be worthwhile to review this recent thread on R-Devel:
https://stat.ethz.ch/pipermail/r-devel/2018-July/076377.html
which touches upon a subtly related topic vis-a-vis NaN handling.
Regards,
Marc Schwartz
On Aug 22, 2018, at 10:55 AM, Bert Gunter <bgunter.4...@gmail.com> wrote:
... And FWIW (not much, I agree), note that if z = numeric(0) and sum(z) =
0, then mean(z) = NaN makes sense, as length(z) = 0, so dividing by 0 gives
NaN. So you can see the sorts of issues you may need to consider.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Aug 22, 2018 at 7:47 AM Bert Gunter <bgunter.4...@gmail.com> wrote:
Actually, the dissonance is a bit more basic.
After xxx(...., na.rm=TRUE) with all NA's in ... you have numeric(0). So
what you see is actually:
z <- numeric(0)
mean(z)
[1] NaN
median(z)
[1] NA
sd(z)
[1] NA
sum(z)
[1] 0
etc.
I imagine that there may be more of these little inconsistencies due to
the organic way R evolved over time. What the conventions should be can be
purely a matter of personal opinion in the absence of accepted standards.
But I would look to see what accepted standards were, if any, first.
-- Bert
On Wed, Aug 22, 2018 at 7:34 AM Ivan Calandra <calan...@rgzm.de> wrote:
Dear useRs,
I have just noticed that when input is only NA with na.rm=TRUE, mean()
results in NaN, whereas median() and sd() produce NA. Shouldn't it all
be the same? I think NA makes more sense than NaN in that case.
x <- c(NA, NA, NA) mean(x, na.rm=TRUE) [1] NaN median(x, na.rm=TRUE) [1]
NAsd(x, na.rm=TRUE) [1] NA
Thanks for any feedback.
Best,
Ivan
--
Dr. Ivan Calandra
TraCEr, laboratory for Traceology and Controlled Experiments
MONREPOS Archaeological Research Centre and
Museum for Human Behavioural Evolution
Schloss Monrepos
56567 Neuwied, Germany
+49 (0) 2631 9772-243
https://www.researchgate.net/profile/Ivan_Calandra
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