Please don’t conflate NaN and NA. You should _never_ use NaN unless you’re
working with an Array, not a DataArray.
— John
On Sep 24, 2014, at 7:48 AM, muraveill <murave...@gmail.com> wrote:
> @data([NaN]) already correctly returns DataArray(Float64, 1). If people mix
> NA's inside, it should return an Any type.
>
> The problem is when it comes from data that is all NA in some parts, like
> results of statistical tests with zero variance etc., and you want
> @data(subset_of_the_data). But stats package should return NaN's instead of
> NA's. And if NA's are already in the file (as text), like in R one should be
> able to decide what string will be converted to NA (by default, "NA"), and
> what is converted to NaN (default "NaN").
>
> Maybe the OP wanted to use NaN instead.
>
> On Wednesday, 24 September 2014 16:32:04 UTC+2, John Myles White wrote:
> I think that DataArray{Any, 1} is probably the best thing you could possibly
> do.
>
> But it’s still going to cause people lots of problems, because there’s almost
> never a time when you’d want to work with DataArray{Any, 1}.
>
> At some point, we have to improve the @data macro.
>
> But for this use case, I suspect people are much better off using
>
> DataArray(Float64, 1)
>
> or something similar to produce an all-NA array of type T and size S.
>
> — John
>
> On Sep 24, 2014, at 7:29 AM, muraveill <mura...@gmail.com> wrote:
>
>> I was about to say DataArray{NAtype,1}. But then the type cannot be changed
>> according to what is added to it, right ?
>> Then DataArray{Any,1}. Just as @data(["asdf" NA; NA 1.4]).
>>
>> On Wednesday, 24 September 2014 16:25:17 UTC+2, John Myles White wrote:
>> Naivete isn’t a big deal. Just try to be very precise. Any literal in Julia
>> should produce a value V of type T.
>>
>> What’s the type T that @data([NA]) would produce?
>>
>> — John
>>
>> On Sep 24, 2014, at 7:22 AM, muraveill <mura...@gmail.com> wrote:
>>
>> > To my naive view, a data array with cells containing ony value NA. Well,
>> > it works with numbers, why not NA. The error thrown is the same in two
>> > dimensions with arrays of length > 1.
>>
>
