Thanks, but these days I'd say Simon Kornblith deserves the credit for what's
good about DataArrays.
-- John
On Sep 25, 2014, at 8:11 AM, Li Zhang wrote:
> I would very much like to contribute, but i am not sure if i had time, some
> projects are keeping me busy. would to look at it when i h
I would very much like to contribute, but i am not sure if i had time, some
projects are keeping me busy. would to look at it when i have spare time.
By the way, john, great work for julia statistics:)
On Tuesday, September 23, 2014 9:11:20 PM UTC-4, Li Zhang wrote:
>
>
>
> a=@data([NA,3,5,7,NA
Would be great to submit a pull request implementing the missing funtionality.
-- John
On Sep 24, 2014, at 6:06 PM, Li Zhang wrote:
> i tried methods in base for Dequeues, but it seems some of them are not
> implemented for DataArray.
> For example:
>
> a=@data([NA,3,5,7,NA,3,7])
> b=copy(a[
i tried methods in base for Dequeues, but it seems some of them are not
implemented for DataArray.
For example:
a=@data([NA,3,5,7,NA,3,7])
b=copy(a[2:end])
append!(b,[NA])
append! works, but prepend! gives no methods error.
also deleteat! works but insert! no methods.
anyway, other methods wo
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 wrote:
> @data([NaN]) already correctly returns DataArray(Float64, 1). If people mix
> NA's inside, it should return an Any type.
>
@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 stat
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
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 ver
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 wrote:
> To my naive view, a data array with cells containing ony value NA. Well, it
julia> @data([NA NA NA; NA NA NA])
ERROR: Type of literal data cannot be inferred
julia> @data([NA NA NA; NA NA 1])
2x3 DataArray{Int64,2}:
NA NA NA
NA NA 1
On Wednesday, 24 September 2014 16:22:48 UTC+2, muraveill wrote:
>
> To my naive view, a data array with cells containing ony value N
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.
What would @data([NA]) even mean?
— John
On Sep 24, 2014, at 7:12 AM, muraveill wrote:
> It looks like a bug that @data([NA]) throws an error, should an issue be
> filed ?
It looks like a bug that @data([NA]) throws an error, should an issue be
filed ?
b = [@data([4]),a[1:end-1]]
b = [@data([NA,4]),a[1:end-1]]
work and return a DataArray.
But
b = [@data([NA]),a[1:end-1]]
says "ERROR: Type of literal data cannot be inferred" and I don't get why.
Maybe you know how to fix the latter ?
On Wednesday, 24 September 2014 03:11:20 UTC+2, Li Zhang wr
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