issue_comments: 178297275
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| 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/issues/738#issuecomment-178297275 | https://api.github.com/repos/pydata/xarray/issues/738 | 178297275 | MDEyOklzc3VlQ29tbWVudDE3ODI5NzI3NQ== | 1217238 | 2016-02-02T01:32:27Z | 2016-02-02T01:32:27Z | MEMBER | Unfortunately, NumPy has no integer type that can support missing values. This leaves us in a difficult situation for integer types. So, we've copied the approach from pandas of upcasting integers to floats when we need to add NaNs: http://pandas.pydata.org/pandas-docs/stable/gotchas.html#nan-integer-na-values-and-na-type-promotions http://xarray.pydata.org/en/stable/computation.html#missing-values (this could use a reference to the aforementioned pandas docs) Conversion from complex to object is certainly not what we want, though, because NaN is a perfectly valid complex number. A fix to A contribution here would definitely be appreciated! We have made some improvements to complex number support recently but it definitely gets less use. |
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