> peter dalgaard
> on Tue, 26 Jul 2016 23:30:31 +0200 writes:
>> On 26 Jul 2016, at 22:26 , Hadley Wickham
>> wrote:
>>
>> On Tue, Jul 26, 2016 at 3:24 AM, Martin Maechler
>> wrote:
>>>
> ...
>> To me, this would be the most sensible default behavio
Agh. I've argued elsewhere that the default behaviour should be to
fail, and the user should take the responsibility to explicitly handle
the missing values, even if that simply be by changing the argument.
Probably Peter and I have different experiences with the completeness
of datasets, but anyt
> On 26 Jul 2016, at 22:26 , Hadley Wickham wrote:
>
> On Tue, Jul 26, 2016 at 3:24 AM, Martin Maechler
> wrote:
>>
...
> To me, this would be the most sensible default behaviour, but I
> realise it's too late to change without breaking many existing
> expectations.
Probably.
Re. the defaul
> I think that's a bit too strict for me, so I wrote my own:
>
> na.warn <- function(object, ...) {
> missing <- complete.cases(object)
> if (any(missing)) {
> warning("Dropping ", sum(missing), " rows with missing values",
> call. = FALSE)
> }
>
> na.exclude(object, ...)
> }
That shou
On Tue, Jul 26, 2016 at 3:24 AM, Martin Maechler
wrote:
> I have been asked (in private)
Martin was very polite to not share my name, but it was me :)
> > Hi Martin,
>
> y <- c(1, 2, 3, NA, 4)
> x <- c(1, 2, 2, 1, 1)
>
> t.test(y ~ x)
> lm(y ~ x)
>
> > Normally, most R fu
I have been asked (in private)
> Hi Martin,
y <- c(1, 2, 3, NA, 4)
x <- c(1, 2, 2, 1, 1)
t.test(y ~ x)
lm(y ~ x)
> Normally, most R functions follow the principle that
> "missings should never silently go missing". Do you have
> any background on why these functi
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