html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/2618#issuecomment-449070341,https://api.github.com/repos/pydata/xarray/issues/2618,449070341,MDEyOklzc3VlQ29tbWVudDQ0OTA3MDM0MQ==,1217238,2018-12-20T17:13:19Z,2018-12-20T17:13:19Z,MEMBER,"xarray will autoconvert a masked array into a numpy array with NaNs. It
probably doesn't make a difference where this happens.

On Thu, Dec 20, 2018 at 9:04 AM Fabien Maussion <notifications@github.com>
wrote:

> Do we really want a np.masked_array or do we just want an array with
> np.Nans in it? I prefer nans, but I guess the downside is type conversion
> for ints?
>
> Masked arrays come with huge performance drops, I don't think we should
> use these.
>
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