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  • Masking and preserving int type · 5 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1115275328 https://github.com/pydata/xarray/issues/3955#issuecomment-1115275328 https://api.github.com/repos/pydata/xarray/issues/3955 IC_kwDOAMm_X85CecBA dcherian 2448579 2022-05-02T19:25:42Z 2022-05-02T19:25:42Z MEMBER

Closing as an upstream issue. We need either numpy to add support or for pandas extensionarrays to support the necssary protocols (#5287)

 
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   Masking and preserving int type 596352097
1114799000 https://github.com/pydata/xarray/issues/3955#issuecomment-1114799000 https://api.github.com/repos/pydata/xarray/issues/3955 IC_kwDOAMm_X85CcnuY stale[bot] 26384082 2022-05-02T12:37:50Z 2022-05-02T12:37:50Z NONE

In order to maintain a list of currently relevant issues, we mark issues as stale after a period of inactivity

If this issue remains relevant, please comment here or remove the stale label; otherwise it will be marked as closed automatically

 
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   Masking and preserving int type 596352097
611321868 https://github.com/pydata/xarray/issues/3955#issuecomment-611321868 https://api.github.com/repos/pydata/xarray/issues/3955 MDEyOklzc3VlQ29tbWVudDYxMTMyMTg2OA== shoyer 1217238 2020-04-09T04:30:44Z 2020-04-09T04:30:55Z MEMBER

I would love to have support for integer NA values in xarray, but I don't think we want to build it into xarray.

Ideally this would either be built into NumPy (i.e., with a custom dtype, which will require some work before its possible) or someone could build an "integer with NA" duckarray, which could implement the various NumPy protocols such as __array_function__. The later is a bit less elegant but could be done today with very few changes in xarray.

 
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   Masking and preserving int type 596352097
610808232 https://github.com/pydata/xarray/issues/3955#issuecomment-610808232 https://api.github.com/repos/pydata/xarray/issues/3955 MDEyOklzc3VlQ29tbWVudDYxMDgwODIzMg== zxdawn 30388627 2020-04-08T07:51:41Z 2020-04-08T07:51:41Z NONE

@kmuehlbauer Thanks, Nice trick! It works well for this situation.

 
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   Masking and preserving int type 596352097
610799451 https://github.com/pydata/xarray/issues/3955#issuecomment-610799451 https://api.github.com/repos/pydata/xarray/issues/3955 MDEyOklzc3VlQ29tbWVudDYxMDc5OTQ1MQ== kmuehlbauer 5821660 2020-04-08T07:31:26Z 2020-04-08T07:42:03Z MEMBER

There has been a lot of discussion about the int vs nan problem in the past, here one issue #1194. My question for xarray-devs would be too, if there is some idea on adapting to the pandas scheme?

In the time being, you might just go the other way round (isel before where) and this little hack:

```python

overwrite fill_values with 0

sub = xr.where(z_indices == fill_value, 0, z_indices)

isel with sub and mask with where

indexed_array = val_arr.isel(z=sub).where(z_indices != fill_value) `` Update: Nevermind, this will make theindexed_arraya float. You might use the samewhere-machinery and overwrite with afill_value ` of your liking:

```python

overwrite fill_values with 0

sub = xr.where(z_indices == fill_value, 0, z_indices)

isel with sub and mask with where

indexed_array = val_arr.isel(z=sub) indexed_array = xr.where(z_indices == fill_value, fill_value, indexed_array) ``` I can't immediately see, but there might be a cleaner way to achieve this.

 
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   Masking and preserving int type 596352097

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