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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
366626025 MDU6SXNzdWUzNjY2MjYwMjU= 2461 Set one-dimensional data variable as dimension coordinate? nedclimaterisk 43126798 closed 0     13 2018-10-04T05:19:25Z 2019-11-21T23:57:15Z 2018-10-04T06:22:03Z CONTRIBUTOR      

Code Sample

I have this dataset, and I'd like to make it indexable by time:

python <xarray.Dataset> Dimensions: (station_observations: 46862) Dimensions without coordinates: station_observations Data variables: time (station_observations) datetime64[ns] ... SNOW_ON_THE_GROUND (station_observations) float64 ... ONE_DAY_SNOW (station_observations) float64 ... ONE_DAY_RAIN (station_observations) float64 ... ONE_DAY_PRECIPITATION (station_observations) float64 ... MIN_TEMP (station_observations) float64 ... MAX_TEMP (station_observations) float64 ... Attributes: elevation: 15.0

Problem description

I expected to be able to use ds.set_coords to make the time variable an indexable coordinate. The variable IS converted to a coordinate, but it is not a dimension coordinate, so I can't index with it. I can use assign_coords(station_observations=ds.time) to make station_observations indexable by time, but then the name in semantically wrong, and the time variable still exists, which makes the code harder to maintain.

Expected Output

```python ds.set_coords('time', inplace=True) <xarray.Dataset> Dimensions: (station_observations: 46862) Coordinates: time (station_observations) datetime64[ns] ... Dimensions without coordinates: station_observations Data variables: SNOW_ON_THE_GROUND (station_observations) float64 ... ONE_DAY_SNOW (station_observations) float64 ... ONE_DAY_RAIN (station_observations) float64 ... ONE_DAY_PRECIPITATION (station_observations) float64 ... MIN_TEMP (station_observations) float64 ... MAX_TEMP (station_observations) float64 ... Attributes: elevation: 15.0

In [95]: ds.sel(time='1896') ValueError: dimensions or multi-index levels ['time'] do not exist ```

with assign_coords:

```python In [97]: ds=ds.assign_coords(station_observations=ds.time)

In [98]: ds.sel(station_observations='1896') Out[98]: <xarray.Dataset> Dimensions: (station_observations: 366) Coordinates: * station_observations (station_observations) datetime64[ns] 1896-01-01 ... Data variables: time (station_observations) datetime64[ns] ... SNOW_ON_THE_GROUND (station_observations) float64 ... ONE_DAY_SNOW (station_observations) float64 ... ONE_DAY_RAIN (station_observations) float64 ... ONE_DAY_PRECIPITATION (station_observations) float64 ... MIN_TEMP (station_observations) float64 ... MAX_TEMP (station_observations) float64 ... Attributes: elevation: 15.0 ``` works correctly, but looks ugly. It would be nice if the time variable could be assigned as a dimension directly. I can drop the time variable and rename the station_observations, but it's a little annoying to do so.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.6.final.0 python-bits: 64 OS: Linux OS-release: 4.16.0-041600-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_AU.UTF-8 LOCALE: en_AU.UTF-8 xarray: 0.10.2 pandas: 0.22.0 numpy: 1.13.3 scipy: 0.19.1 netCDF4: 1.3.1 h5netcdf: None h5py: None Nio: None zarr: None bottleneck: 1.2.0 cyordereddict: None dask: 0.16.0 distributed: None matplotlib: 2.1.1 cartopy: None seaborn: None setuptools: 39.0.1 pip: 9.0.1 conda: None pytest: None IPython: 5.5.0 sphinx: None 
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   completed xarray 13221727 issue
456769766 MDU6SXNzdWU0NTY3Njk3NjY= 3026 Rename dims independently from coords? nedclimaterisk 43126798 closed 0     11 2019-06-17T06:48:40Z 2019-07-02T20:24:55Z 2019-07-02T20:24:55Z CONTRIBUTOR      

I have a dataset that looks like this:

python <xarray.Dataset> Dimensions: (lat: 226, lon: 261, time: 7300) Coordinates: * lat (lat) float32 -32.0 -31.9 -31.8 -31.7 ... -9.700001 -9.6 -9.5 * lon (lon) float32 132.0 132.1 132.2 132.3 ... 157.7 157.8 157.9 158.0 * time (time) object 1980-01-01 15:00:00 ... 1999-12-31 15:00:00 Data variables: rnd24 (time, lat, lon) float32 ...

Problem description

I would like to be able to rename the dataset dimensions, without renaming the coordinates.

Expected Output

python <xarray.Dataset> Dimensions: (y: 226, x: 261, time: 7300) Coordinates: * lat (y) float32 -32.0 -31.9 -31.8 -31.7 ... -9.700001 -9.6 -9.5 * lon (x) float32 132.0 132.1 132.2 132.3 ... 157.7 157.8 157.9 158.0 * time (time) object 1980-01-01 15:00:00 ... 1999-12-31 15:00:00 Data variables: rnd24 (time, y, x) float32 ...

As far as I can tell, there is no way to do this. I can rename the existing dims/coords to x/y, and then manually create new coordinates that are copies of x and y, which gets me to:

python <xarray.Dataset> Dimensions: (time: 7300, x: 261, y: 226) Coordinates: * y (y) float32 -32.0 -31.9 -31.8 -31.7 ... -9.700001 -9.6 -9.5 * x (x) float32 132.0 132.1 132.2 132.3 ... 157.7 157.8 157.9 158.0 * time (time) object 1980-01-01 15:00:00 ... 1999-12-31 15:00:00 lat (y) float32 -32.0 -31.9 -31.8 -31.7 ... -9.700001 -9.6 -9.5 lon (x) float32 132.0 132.1 132.2 132.3 ... 157.7 157.8 157.9 158.0 Data variables: rnd24 (time, y, x) float32 ...

But it doesn't seem to be possible to re-assign the new coordinates as the indexes for the existing dims.

In this case, it may seem a bit redundant, because the coordinates are equal to the grid. But I'm trying to get this output to work with code that also deals with other datasets that have non- rectilinear grids.

 
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   completed xarray 13221727 issue
366711310 MDExOlB1bGxSZXF1ZXN0MjIwMzE2NjY2 2463 Add swap_coords to relevant 'See also' sections nedclimaterisk 43126798 closed 0     3 2018-10-04T09:58:16Z 2018-10-23T05:55:45Z 2018-10-23T05:55:34Z CONTRIBUTOR   0 pydata/xarray/pulls/2463

Minor documentation additions.

  • [ ] Closes #2461 
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     xarray 13221727 pull
371845469 MDExOlB1bGxSZXF1ZXN0MjI0MTk5OTc1 2493 Include multidimensional stacking groupby in docs nedclimaterisk 43126798 closed 0     1 2018-10-19T07:55:15Z 2018-10-23T00:25:45Z 2018-10-23T00:25:35Z CONTRIBUTOR   0 pydata/xarray/pulls/2493

Include short example of multidimensional stack-groupby-apply-unstack methodology.

 
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     xarray 13221727 pull

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