For avoiding unwanted conversions, DataFramesMeta has a PassThrough type
with an alias P. You should be able to do:

mydf[1] = P(Array(mydf[1]))

On Sep 14, 2016 5:17 PM, "Douglas Bates" <[email protected]> wrote:

> Of course, this brings me back to another problem, which is replacing a
> column of a dataframe with an Array without having the Array converted to a
> DataArray or a NullableArray.  I have a large CSV file in which over 99% of
> the columns do not contain nulls.  Because some of the columns contain
> nulls I can't use CSV.read(..., nullable = false) but I do want to convert
> those columns that do not contain nulls to Arrays.
>
> If I try to replace the column as
>
> mydf[1] = Array(mydf[1])
>
> I get a DataArray in the release version of DataFrames.  (I'm not sure
> what happens in your nl/nullable branch).
>
> The way I avoid this is right now is by working with mydf.columns directly
> but I always caution others not to work directly with fields of composite
> types and I should probably follow my own advice.
>
> On Wednesday, September 14, 2016 at 4:07:21 PM UTC-5, Douglas Bates wrote:
>>
>> Thanks.  I didn't try that because I thought that a NullableArray was an
>> Array so that conversion would be a no-op.  I should have tested it.
>>
>> On Wednesday, September 14, 2016 at 4:02:04 PM UTC-5, Milan Bouchet-Valat
>> wrote:
>>>
>>> Le mercredi 14 septembre 2016 à 13:56 -0700, Douglas Bates a écrit :
>>> > I remember someone (Milan?, Alex?) writing a short cal to convert a
>>> > NullableArray to an Array but I can't seem to find it now.  Can
>>> > someone refresh my memory, please?
>>> What do you mean exactly? This works AFAICT:
>>> julia> convert(Array, NullableArray(1:3))
>>> 3-element Array{Int64,1}:
>>>  1
>>>  2
>>>  3
>>>
>>>
>>> Regards
>>>
>> --
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