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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
2278510478 PR_kwDOAMm_X85uhIGP 8998 Zarr: Optimize appending dcherian 2448579 open 0     0 2024-05-03T22:21:44Z 2024-05-03T22:23:34Z   MEMBER   1 pydata/xarray/pulls/8998

Builds on #8997 

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     xarray 13221727 pull
2261844699 PR_kwDOAMm_X85toeXT 8968 Bump dependencies incl `pandas>=2` dcherian 2448579 closed 0     0 2024-04-24T17:42:19Z 2024-04-27T14:17:16Z 2024-04-27T14:17:16Z MEMBER   0 pydata/xarray/pulls/8968
  • [ ] Closes #xxxx
  • [ ] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull
2187743087 PR_kwDOAMm_X85ptH1f 8840 Grouper, Resampler as public api dcherian 2448579 open 0     0 2024-03-15T05:16:05Z 2024-04-21T16:21:34Z   MEMBER   1 pydata/xarray/pulls/8840

Expose Grouper and Resampler as public API

TODO: - [ ] Consider avoiding IndexVariable

  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [x] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull
2228266052 PR_kwDOAMm_X85r24hE 8913 Update hypothesis action to always save the cache dcherian 2448579 closed 0     0 2024-04-05T15:09:35Z 2024-04-05T16:51:05Z 2024-04-05T16:51:03Z MEMBER   0 pydata/xarray/pulls/8913

Update the cache always.

 
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     xarray 13221727 pull
2228319306 I_kwDOAMm_X86E0XRK 8914 swap_dims does not propagate indexes properly dcherian 2448579 open 0     0 2024-04-05T15:36:26Z 2024-04-05T15:36:27Z   MEMBER      

What happened?

Found by hypothesis ``` import xarray as xr import numpy as np

var = xr.Variable(dims="2", data=np.array(['1970-01-01T00:00:00.000000000', '1970-01-01T00:00:00.000000002', '1970-01-01T00:00:00.000000001'], dtype='datetime64[ns]')) var1 = xr.Variable(data=np.array([0], dtype=np.uint32), dims=['1'], attrs={})

state = xr.Dataset() state['2'] = var state = state.stack({"0": ["2"]}) state['1'] = var1 state['1_'] = var1#.copy(deep=True) state = state.swap_dims({"1": "1_"}) xr.testing.assertions._assert_internal_invariants(state, False) ```

This swaps simple pandas indexed dims, but the multi-index that is in the dataset and not affected by the swap_dims op ends up broken.

cc @benbovy

What did you expect to happen?

No response

Minimal Complete Verifiable Example

No response

MVCE confirmation

  • [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.
  • [ ] Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

No response

Anything else we need to know?

No response

Environment

 
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     xarray 13221727 issue
2136709010 I_kwDOAMm_X85_W5eS 8753 Lazy Loading with `DataArray` vs. `Variable` dcherian 2448579 closed 0     0 2024-02-15T14:42:24Z 2024-04-04T16:46:54Z 2024-04-04T16:46:54Z MEMBER      

Discussed in https://github.com/pydata/xarray/discussions/8751

<sup>Originally posted by **ilan-gold** February 15, 2024</sup> My goal is to get a dataset from [custom io-zarr backend lazy-loaded](https://docs.xarray.dev/en/stable/internals/how-to-add-new-backend.html#how-to-support-lazy-loading). But when I declare a `DataArray` based on the `Variable` which uses `LazilyIndexedArray`, everything is read in. Is this expected? I specifically don't want to have to use dask if possible. I have seen https://github.com/aurghs/xarray-backend-tutorial/blob/main/2.Backend_with_Lazy_Loading.ipynb but it's a little bit different. While I have a custom backend array inheriting from `ZarrArrayWrapper`, this example using `ZarrArrayWrapper` directly still highlights the same unexpected behavior of everything being read in. ```python import zarr import xarray as xr from tempfile import mkdtemp import numpy as np from pathlib import Path from collections import defaultdict class AccessTrackingStore(zarr.DirectoryStore): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._access_count = {} self._accessed = defaultdict(set) def __getitem__(self, key): for tracked in self._access_count: if tracked in key: self._access_count[tracked] += 1 self._accessed[tracked].add(key) return super().__getitem__(key) def get_access_count(self, key): return self._access_count[key] def set_key_trackers(self, keys_to_track): if isinstance(keys_to_track, str): keys_to_track = [keys_to_track] for k in keys_to_track: self._access_count[k] = 0 def get_subkeys_accessed(self, key): return self._accessed[key] orig_path = Path(mkdtemp()) z = zarr.group(orig_path / "foo.zarr") z['array'] = np.random.randn(1000, 1000) store = AccessTrackingStore(orig_path / "foo.zarr") store.set_key_trackers(['array']) z = zarr.group(store) arr = xr.backends.zarr.ZarrArrayWrapper(z['array']) lazy_arr = xr.core.indexing.LazilyIndexedArray(arr) # just `.zarray` var = xr.Variable(('x', 'y'), lazy_arr) print('Variable read in ', store.get_subkeys_accessed('array')) # now everything is read in da = xr.DataArray(var) print('DataArray read in ', store.get_subkeys_accessed('array')) ```
 
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   completed xarray 13221727 issue
2224300175 PR_kwDOAMm_X85rpG4S 8907 Trigger hypothesis stateful tests nightly dcherian 2448579 closed 0     0 2024-04-04T02:16:59Z 2024-04-04T02:17:49Z 2024-04-04T02:17:47Z MEMBER   0 pydata/xarray/pulls/8907
  • [ ] Closes #xxxx
  • [ ] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull
2000205407 PR_kwDOAMm_X85fzupc 8467 [skip-ci] dev whats-new dcherian 2448579 closed 0     0 2023-11-18T03:59:29Z 2024-04-03T21:08:45Z 2023-11-18T15:20:37Z MEMBER   0 pydata/xarray/pulls/8467
  • [ ] Closes #xxxx
  • [ ] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull
1989233637 PR_kwDOAMm_X85fOdAk 8446 Remove PseudoNetCDF dcherian 2448579 closed 0     0 2023-11-12T04:29:50Z 2024-04-03T21:08:44Z 2023-11-13T21:53:56Z MEMBER   0 pydata/xarray/pulls/8446

joining the party - [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

 
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     xarray 13221727 pull
2102850331 PR_kwDOAMm_X85lMW8k 8674 Fix negative slicing of Zarr arrays dcherian 2448579 closed 0     0 2024-01-26T20:22:21Z 2024-04-03T21:08:26Z 2024-02-10T02:57:32Z MEMBER   0 pydata/xarray/pulls/8674

Closes #8252 Closes #3921

  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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     xarray 13221727 pull
2148245262 PR_kwDOAMm_X85nmmqX 8777 Return a dataclass from Grouper.factorize dcherian 2448579 closed 0     0 2024-02-22T05:41:29Z 2024-04-03T21:08:25Z 2024-03-15T04:47:30Z MEMBER   0 pydata/xarray/pulls/8777

Toward #8510, builds on #8776

 
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     xarray 13221727 pull
2148164557 PR_kwDOAMm_X85nmU5w 8775 [skip-ci] NamedArray: Add lazy indexing array refactoring plan dcherian 2448579 closed 0     0 2024-02-22T04:25:49Z 2024-04-03T21:08:21Z 2024-02-23T22:20:09Z MEMBER   0 pydata/xarray/pulls/8775

This adds a proposal for decoupling the lazy indexing array machinery, indexing adapter machinery, and Variable's setitem and getitem methods, so that the latter can be migrated to NamedArray.

cc @andersy005 

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     xarray 13221727 pull
2198991054 PR_kwDOAMm_X85qTNFP 8861 upstream-dev CI: Fix interp and cumtrapz dcherian 2448579 closed 0     0 2024-03-21T02:49:40Z 2024-04-03T21:08:17Z 2024-03-21T04:16:45Z MEMBER   0 pydata/xarray/pulls/8861
  • [x] xref #8844
 
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2215539648 PR_kwDOAMm_X85rLW_p 8891 2024.03.0: Add whats-new dcherian 2448579 closed 0     0 2024-03-29T15:01:35Z 2024-03-29T17:07:19Z 2024-03-29T17:07:17Z MEMBER   0 pydata/xarray/pulls/8891   
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     xarray 13221727 pull
2206047573 PR_kwDOAMm_X85qrHyn 8875 Optimize writes to existing Zarr stores. dcherian 2448579 closed 0     0 2024-03-25T15:32:47Z 2024-03-29T14:35:30Z 2024-03-29T14:35:29Z MEMBER   0 pydata/xarray/pulls/8875

We need to read existing variables to make sure we append or write to a region with the right encoding. Currently we decode all arrays in a Zarr group. Instead only decode those arrays for which we require encoding information.

 
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     xarray 13221727 pull
2206385638 PR_kwDOAMm_X85qsSKm 8877 Don't allow overwriting indexes with region writes dcherian 2448579 closed 0     0 2024-03-25T18:13:19Z 2024-03-27T16:24:37Z 2024-03-27T16:24:35Z MEMBER   0 pydata/xarray/pulls/8877
  • [x] Closes #8589
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

cc @slevang 

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2189750364 PR_kwDOAMm_X85p0Epw 8847 pandas 3 MultiIndex fixes dcherian 2448579 closed 0     0 2024-03-16T03:51:06Z 2024-03-20T15:00:20Z 2024-03-20T15:00:18Z MEMBER   0 pydata/xarray/pulls/8847 
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     xarray 13221727 pull
2021856935 PR_kwDOAMm_X85g81gb 8509 Proof of concept - public Grouper objects dcherian 2448579 open 0     0 2023-12-02T04:52:27Z 2024-03-15T05:18:18Z   MEMBER   1 pydata/xarray/pulls/8509

Not for merging, just proof that it can be done nicely :)

Now builds on #8840 ~Builds on an older version of #8507~

Try it out!

```python import xarray as xr from xarray.core.groupers import SeasonGrouper, SeasonResampler

ds = xr.tutorial.open_dataset("air_temperature")

custom seasons!

ds.air.groupby(time=SeasonGrouper(["JF", "MAM", "JJAS", "OND"])).mean()

ds.air.resample(time=SeasonResampler(["DJF", "MAM", "JJAS", "ON"])).count() ```

 
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     xarray 13221727 pull
2187682227 PR_kwDOAMm_X85ps6tB 8839 [skip-ci] Fix upstream-dev env dcherian 2448579 closed 0     0 2024-03-15T04:08:58Z 2024-03-15T04:37:59Z 2024-03-15T04:37:58Z MEMBER   0 pydata/xarray/pulls/8839

upstream-dev env is broken

  • [x] Closes #8623
 
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     xarray 13221727 pull
2187646833 PR_kwDOAMm_X85psy9g 8837 Add dask-expr for windows envs dcherian 2448579 closed 0     0 2024-03-15T03:27:48Z 2024-03-15T04:06:05Z 2024-03-15T04:06:03Z MEMBER   0 pydata/xarray/pulls/8837
  • [x] Closes #8830
  • [ ] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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2184606202 PR_kwDOAMm_X85picsD 8827 Add `dask-expr` to environment-3.12.yml dcherian 2448579 closed 0     0 2024-03-13T18:07:27Z 2024-03-13T20:20:46Z 2024-03-13T20:20:45Z MEMBER   0 pydata/xarray/pulls/8827 
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     xarray 13221727 pull
2148242023 PR_kwDOAMm_X85nml9d 8776 Refactor Grouper objects dcherian 2448579 closed 0     0 2024-02-22T05:38:09Z 2024-03-07T21:50:07Z 2024-03-07T21:50:04Z MEMBER   0 pydata/xarray/pulls/8776

Some refactoring towards the Grouper refactor described in #8510

  1. Rename to Resampler from ResampleGrouper
  2. Refactor to a single "ResolvedGrouper" object that encapsulates the underling Grouper/Resampler object: UniqueGrouper, BinGrouper, or TimeResampler.
 
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     xarray 13221727 pull
2135011804 I_kwDOAMm_X85_QbHc 8748 release v2024.02.0 dcherian 2448579 closed 0 keewis 14808389   0 2024-02-14T19:08:38Z 2024-02-18T22:52:15Z 2024-02-18T22:52:15Z MEMBER      

What is your issue?

Thanks to @keewis for volunteering at today's meeting :()

 
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   completed xarray 13221727 issue
2098626592 PR_kwDOAMm_X85k-Mnt 8657 groupby: Don't set `method` by default on flox>=0.9 dcherian 2448579 closed 0     0 2024-01-24T16:20:57Z 2024-01-26T16:54:25Z 2024-01-26T16:54:23Z MEMBER   0 pydata/xarray/pulls/8657
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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     xarray 13221727 pull
2086607437 I_kwDOAMm_X858XxpN 8616 new release 2024.01.0 dcherian 2448579 closed 0     0 2024-01-17T17:03:20Z 2024-01-17T19:21:12Z 2024-01-17T19:21:12Z MEMBER      

What is your issue?

Thanks @TomNicholas for volunteering to drive this release!

 
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   completed xarray 13221727 issue
2065788086 PR_kwDOAMm_X85jOw74 8585 Enable Zarr V3 tests in all CI runs. dcherian 2448579 closed 0     0 2024-01-04T14:45:44Z 2024-01-05T17:53:08Z 2024-01-05T17:53:06Z MEMBER   0 pydata/xarray/pulls/8585

🤦🏾‍♂️

Spotted in https://github.com/pydata/xarray/pull/8460

Builds on #8586 

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     xarray 13221727 pull
2064420057 I_kwDOAMm_X857DIzZ 8581 bump min versions dcherian 2448579 closed 0     0 2024-01-03T17:45:10Z 2024-01-05T16:13:16Z 2024-01-05T16:13:15Z MEMBER      

What is your issue?

Looks like we can bump a number of min versions: ``` Package Required Policy Status

cartopy 0.20 (2021-09-17) 0.21 (2022-09-10) < dask-core 2022.7 (2022-07-08) 2022.12 (2022-12-02) < distributed 2022.7 (2022-07-08) 2022.12 (2022-12-02) < flox 0.5 (2022-05-03) 0.6 (2022-10-12) < iris 3.2 (2022-02-15) 3.4 (2022-12-01) < matplotlib-base 3.5 (2021-11-18) 3.6 (2022-09-16) < numba 0.55 (2022-01-14) 0.56 (2022-09-28) < numpy 1.22 (2022-01-03) 1.23 (2022-06-23) < packaging 21.3 (2021-11-18) 22.0 (2022-12-08) < pandas 1.4 (2022-01-22) 1.5 (2022-09-19) < scipy 1.8 (2022-02-06) 1.9 (2022-07-30) < seaborn 0.11 (2020-09-08) 0.12 (2022-09-06) < typing_extensions 4.3 (2022-07-01) 4.4 (2022-10-07) < zarr 2.12 (2022-06-23) 2.13 (2022-09-27) < ```

 
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   completed xarray 13221727 issue
2065809896 PR_kwDOAMm_X85jO1oX 8586 Bump min deps. dcherian 2448579 closed 0     0 2024-01-04T14:59:05Z 2024-01-05T16:13:16Z 2024-01-05T16:13:14Z MEMBER   0 pydata/xarray/pulls/8586
  • [x] Closes #8581
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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     xarray 13221727 pull
2052952379 I_kwDOAMm_X856XZE7 8568 Raise when assigning attrs to virtual variables (default coordinate arrays) dcherian 2448579 open 0     0 2023-12-21T19:24:11Z 2023-12-21T19:24:19Z   MEMBER      

Discussed in https://github.com/pydata/xarray/discussions/8567

<sup>Originally posted by **matthew-brett** December 21, 2023</sup> Sorry for the introductory question, but we (@ivanov and I) ran into this behavior while experimenting: ```python import numpy as np data = np.zeros((3, 4, 5)) ds = xr.DataArray(data, dims=('i', 'j', 'k')) print(ds['k'].attrs) ``` This shows `{}` as we might reasonably expect. But then: ```python ds['k'].attrs['foo'] = 'bar' print(ds['k'].attrs) ``` This also gives `{}`, which we found surprising. We worked out why that was, after a little experimentation (the default coordinate arrays seems to get created on the fly and garbage collected immediately). But it took us a little while. Is that as intended? Is there a way of making this less confusing? Thanks for any help. 
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     xarray 13221727 issue
2047617215 PR_kwDOAMm_X85iUJ7y 8560 Adapt map_blocks to use new Coordinates API dcherian 2448579 closed 0     0 2023-12-18T23:11:55Z 2023-12-20T17:11:18Z 2023-12-20T17:11:16Z MEMBER   0 pydata/xarray/pulls/8560

Fixes roundtripping of string dtype indexes

  • [x] Tests added
 
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     xarray 13221727 pull
1954809370 I_kwDOAMm_X850hAYa 8353 Update benchmark suite for asv 0.6.1 dcherian 2448579 open 0     0 2023-10-20T18:13:22Z 2023-12-19T05:53:21Z   MEMBER      

The new asv version comes with decorators for parameterizing and skipping, and the ability to use mamba to create environments.

https://github.com/airspeed-velocity/asv/releases

https://asv.readthedocs.io/en/v0.6.1/writing_benchmarks.html#skipping-benchmarks

This might help us reduce benchmark times a bit, or at least simplify the code some.

 
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     xarray 13221727 issue
2033054792 PR_kwDOAMm_X85hi5U2 8532 Whats-new for 2023.12.0 dcherian 2448579 closed 0     0 2023-12-08T17:29:47Z 2023-12-08T19:36:28Z 2023-12-08T19:36:26Z MEMBER   0 pydata/xarray/pulls/8532
  • [ ] Closes #xxxx
  • [ ] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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     xarray 13221727 pull
1989588884 I_kwDOAMm_X852lreU 8448 mypy 1.7.0 raising errors dcherian 2448579 closed 0     0 2023-11-12T21:41:43Z 2023-12-01T22:02:22Z 2023-12-01T22:02:22Z MEMBER      

What happened?

xarray/namedarray/core.py:758: error: Value of type Never is not indexable [index] xarray/core/alignment.py:684: error: Unused "type: ignore" comment [unused-ignore] xarray/core/alignment.py:1156: error: Unused "type: ignore" comment [unused-ignore] xarray/core/dataset.py: note: In member "sortby" of class "Dataset": xarray/core/dataset.py:7967: error: Incompatible types in assignment (expression has type "tuple[Alignable, ...]", variable has type "tuple[DataArray, ...]") [assignment] xarray/core/dataset.py:7979: error: "Alignable" has no attribute "isel" [attr-defined]

 
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   completed xarray 13221727 issue
2003229011 PR_kwDOAMm_X85f9xPG 8472 Avoid duplicate Zarr array read dcherian 2448579 closed 0     0 2023-11-21T00:16:34Z 2023-12-01T02:58:22Z 2023-12-01T02:47:03Z MEMBER   0 pydata/xarray/pulls/8472

We already get the underlying Zarr array in https://github.com/pydata/xarray/blob/bb8511e0894020e180d95d2edb29ed4036ac6447/xarray/backends/zarr.py#L529-L531

and then pass it to open_store_variable. Just pass that array down to ZarrArrayWrapper instead of reading it from the datastore again.

 
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     xarray 13221727 pull
2015530249 PR_kwDOAMm_X85gnO8L 8489 Minor to_zarr optimizations dcherian 2448579 closed 0     0 2023-11-28T23:56:32Z 2023-12-01T02:20:19Z 2023-12-01T02:18:18Z MEMBER   0 pydata/xarray/pulls/8489

Avoid repeatedly pinging a remote store by requesting keys at one go.

 
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     xarray 13221727 pull
1997656427 PR_kwDOAMm_X85frEdb 8461 2023.11.0 Whats-new dcherian 2448579 closed 0     0 2023-11-16T19:55:12Z 2023-11-17T21:02:22Z 2023-11-17T21:02:20Z MEMBER   0 pydata/xarray/pulls/8461   
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1997136566 PR_kwDOAMm_X85fpRL3 8458 Pin mypy < 1.7 dcherian 2448579 closed 0     0 2023-11-16T15:31:26Z 2023-11-16T17:29:04Z 2023-11-16T17:29:03Z MEMBER   0 pydata/xarray/pulls/8458

xref #8448 get back to green checks for now.

 
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1995186323 PR_kwDOAMm_X85finmE 8452 [skip-ci] Small updates to IO docs. dcherian 2448579 closed 0     0 2023-11-15T17:05:47Z 2023-11-16T15:19:59Z 2023-11-16T15:19:57Z MEMBER   0 pydata/xarray/pulls/8452

Also fixes the RTD failure on main

 
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     xarray 13221727 pull
1635949876 PR_kwDOAMm_X85MpxlL 7659 Redo whats-new for 2023.03.0 dcherian 2448579 closed 0     0 2023-03-22T15:02:38Z 2023-11-06T04:25:54Z 2023-03-22T15:42:49Z MEMBER   0 pydata/xarray/pulls/7659   
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     xarray 13221727 pull
1630533356 PR_kwDOAMm_X85MXo4e 7643 Whats-new for release 2023.03.0 dcherian 2448579 closed 0     0 2023-03-18T19:14:55Z 2023-11-06T04:25:53Z 2023-03-20T15:57:36Z MEMBER   0 pydata/xarray/pulls/7643   
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     xarray 13221727 pull
1533942791 PR_kwDOAMm_X85HahUq 7440 v2023.01.0 whats-new dcherian 2448579 closed 0     0 2023-01-15T18:20:28Z 2023-11-06T04:25:52Z 2023-01-18T21:18:49Z MEMBER   0 pydata/xarray/pulls/7440

Should update the date and delete empty sections before merging

 
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     xarray 13221727 pull
1975400777 PR_kwDOAMm_X85efqSl 8408 Generalize explicit_indexing_adapter dcherian 2448579 open 0     0 2023-11-03T03:29:40Z 2023-11-03T03:53:25Z   MEMBER   1 pydata/xarray/pulls/8408

Use as_indexable instead of NumpyIndexingAdapter

 
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     xarray 13221727 pull
1942673099 PR_kwDOAMm_X85cxp-D 8305 Update labeler.yml to add NamedArray dcherian 2448579 closed 0     0 2023-10-13T21:39:56Z 2023-10-14T06:47:08Z 2023-10-14T06:47:07Z MEMBER   0 pydata/xarray/pulls/8305
  • [ ] Closes #xxxx
  • [ ] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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1942893480 I_kwDOAMm_X85zzjOo 8306 keep_attrs for NamedArray dcherian 2448579 open 0     0 2023-10-14T02:29:54Z 2023-10-14T02:31:35Z   MEMBER      

What is your issue?

Copying over @max-sixty's comment from https://github.com/pydata/xarray/pull/8304#discussion_r1358873522

I haven't been in touch with the NameArray discussions so forgive a glib comment — but re https://github.com/pydata/xarray/issues/3891 — this would be a "once-in-a-library" opportunity to always retain attrs in aggregations, removing the keep_attrs option in methods.

(Xarray could still handle them as it wished, so xarray's external interface wouldn't need to change immediately...)

@pydata/xarray Should we just delete the keep_attrs kwarg completely for NamedArray and always propagate attrs? obj.attrs.clear() seems just as easy to type.

 
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     xarray 13221727 issue
1874773066 PR_kwDOAMm_X85ZMtUP 8126 Allow creating DataArrays with nD coordinate variables dcherian 2448579 closed 0     0 2023-08-31T04:40:37Z 2023-09-22T12:48:38Z 2023-09-22T12:48:34Z MEMBER   0 pydata/xarray/pulls/8126
  • [x] Closes #8106
  • [x] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst

cc @blaylockbk 

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     xarray 13221727 pull
1902086612 PR_kwDOAMm_X85aoYuf 8206 flox: Set fill_value=np.nan always. dcherian 2448579 open 0     0 2023-09-19T02:19:49Z 2023-09-19T02:23:26Z   MEMBER   1 pydata/xarray/pulls/8206
  • [x] Closes #8090
  • [x] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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1888576440 I_kwDOAMm_X85wkWO4 8162 Update group by multi index dcherian 2448579 open 0     0 2023-09-09T04:50:29Z 2023-09-09T04:50:39Z   MEMBER      

ideally GroupBy._infer_concat_args() would return a xr.Coordinates object that contains both the coordinate(s) and their (multi-)index to assign to the result (combined) object.

The goal is to avoid calling create_default_index_implicit(coord) below where coord is a pd.MultiIndex or a single IndexVariable wrapping a multi-index. If coord is a Coordinates object, we could do combined = combined.assign_coords(coord) instead.

https://github.com/pydata/xarray/blob/e2b6f3468ef829b8a83637965d34a164bf3bca78/xarray/core/groupby.py#L1573-L1587

There are actually more general issues:

  • The group parameter of Dataset.groupby being a single variable or variable name, it won't be possible to do groupby on a full pandas multi-index once we drop its dimension coordinate (#8143). How can we still support it? Maybe passing a dimension name to group and check that there's only one index for that dimension?
  • How can we support custom, multi-coordinate indexes with groupby? I don't have any practical example in mind, but in theory just passing a single coordinate name as group will invalidate the index. Should we drop the index in the result? Or, like suggested above pass a dimension name as group and check the index?

Originally posted by @benbovy in https://github.com/pydata/xarray/issues/8140#issuecomment-1709775666

 
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     xarray 13221727 issue
1812504689 I_kwDOAMm_X85sCKBx 8006 Fix documentation about datetime_unit of xarray.DataArray.differentiate dcherian 2448579 closed 0     0 2023-07-19T18:31:10Z 2023-09-01T09:37:15Z 2023-09-01T09:37:15Z MEMBER      

Should say that Y and M cannot be supported with datetime64

Discussed in https://github.com/pydata/xarray/discussions/8000

<sup>Originally posted by **jesieleo** July 19, 2023</sup> I have a piece of data that looks like this ``` <xarray.Dataset> Dimensions: (time: 612, LEV: 15, latitude: 20, longitude: 357) Coordinates: * time (time) datetime64[ns] 1960-01-15 1960-02-15 ... 2010-12-15 * LEV (LEV) float64 5.01 15.07 25.28 35.76 ... 149.0 171.4 197.8 229.5 * latitude (latitude) float64 -4.75 -4.25 -3.75 -3.25 ... 3.75 4.25 4.75 * longitude (longitude) float64 114.2 114.8 115.2 115.8 ... 291.2 291.8 292.2 Data variables: u (time, LEV, latitude, longitude) float32 ... Attributes: (12/30) cdm_data_type: Grid Conventions: COARDS, CF-1.6, ACDD-1.3 creator_email: chepurin@umd.edu creator_name: APDRC creator_type: institution creator_url: https://www.atmos.umd.edu/~ocean/ ... ... standard_name_vocabulary: CF Standard Name Table v29 summary: Simple Ocean Data Assimilation (SODA) soda po... time_coverage_end: 2010-12-15T00:00:00Z time_coverage_start: 1983-01-15T00:00:00Z title: SODA soda pop2.2.4 [TIME][LEV][LAT][LON] Westernmost_Easting: 118.25 ``` when i try to use xarray.DataArray.differentiate `data.u.differentiate('time',datetime_unit='M')` will appear ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "D:\Anaconda3\lib\site-packages\xarray\core\dataarray.py", line 3609, in differentiate ds = self._to_temp_dataset().differentiate(coord, edge_order, datetime_unit) File "D:\Anaconda3\lib\site-packages\xarray\core\dataset.py", line 6372, in differentiate coord_var = coord_var._to_numeric(datetime_unit=datetime_unit) File "D:\Anaconda3\lib\site-packages\xarray\core\variable.py", line 2428, in _to_numeric numeric_array = duck_array_ops.datetime_to_numeric( File "D:\Anaconda3\lib\site-packages\xarray\core\duck_array_ops.py", line 466, in datetime_to_numeric array = array / np.timedelta64(1, datetime_unit) TypeError: Cannot get a common metadata divisor for Numpy datatime metadata [ns] and [M] because they have incompatible nonlinear base time units. ``` Would you please told me is this a BUG?
 
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   completed xarray 13221727 issue
1861692451 PR_kwDOAMm_X85YgtYD 8098 [skip-ci] dev whats-new dcherian 2448579 closed 0     0 2023-08-22T15:20:54Z 2023-08-22T20:46:29Z 2023-08-22T20:46:29Z MEMBER   0 pydata/xarray/pulls/8098   
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1855338426 PR_kwDOAMm_X85YLRQH 8081 Add 2023.08.0 whats-new dcherian 2448579 closed 0     0 2023-08-17T16:36:06Z 2023-08-18T20:12:27Z 2023-08-18T20:12:25Z MEMBER   0 pydata/xarray/pulls/8081   
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1829952467 PR_kwDOAMm_X85W1yq4 8033 Reduce pre-commit update frequency to monthly from weekly. dcherian 2448579 closed 0     0 2023-07-31T20:16:05Z 2023-08-01T16:48:12Z 2023-08-01T16:48:10Z MEMBER   0 pydata/xarray/pulls/8033

We could even go down to quarterly

 
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     xarray 13221727 pull
1824824446 I_kwDOAMm_X85sxJx- 8025 Support Groupby first, last with flox dcherian 2448579 open 0     0 2023-07-27T17:07:51Z 2023-07-27T19:08:06Z   MEMBER      

Is your feature request related to a problem?

flox recently added support for first, last, nanfirst, nanlast. So we should support that on the Xarray GroupBy object.

 
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     xarray 13221727 issue
1642299599 I_kwDOAMm_X85h44DP 7683 automatically chunk in groupby binary ops dcherian 2448579 closed 0     0 2023-03-27T15:14:09Z 2023-07-27T16:41:35Z 2023-07-27T16:41:34Z MEMBER      

What happened?

From https://discourse.pangeo.io/t/xarray-unable-to-allocate-memory-how-to-size-up-problem/3233/4

Consider ``` python

ds is dataset with big dask arrays

mean = ds.groupby("time.day").mean() mean.to_netcdf() mean = xr.open_dataset(...)

ds.groupby("time.day") - mean ```

In GroupBy._binary_op https://github.com/pydata/xarray/blob/39caafae4452f5327a7cd671b18d4bb3eb3785ba/xarray/core/groupby.py#L616

we will eagerly construct other that is of the same size as ds.

What did you expect to happen?

I think the only solution is to automatically chunk if ds has dask arrays, and other (or mean) isn't backed by dask arrays. A chunk size of 1 seems sensible.

Minimal Complete Verifiable Example

No response

MVCE confirmation

  • [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

Environment

 
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   completed xarray 13221727 issue
1812646094 PR_kwDOAMm_X85V7g7q 8007 Update copyright year in README dcherian 2448579 closed 0     0 2023-07-19T20:00:50Z 2023-07-20T21:13:27Z 2023-07-20T21:13:26Z MEMBER   0 pydata/xarray/pulls/8007   
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     xarray 13221727 pull
1797636782 I_kwDOAMm_X85rJcKu 7976 Explore updating colormap code dcherian 2448579 closed 0     0 2023-07-10T21:51:30Z 2023-07-11T13:49:54Z 2023-07-11T13:49:53Z MEMBER      

What is your issue?

See https://github.com/matplotlib/matplotlib/issues/16296

Looks like the MPL API may have advanced enough that we can delete some of our use of private attributes.

 
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   completed xarray 13221727 issue
1701070898 PR_kwDOAMm_X85QCzA1 7830 Fix .groupby(multi index level) dcherian 2448579 closed 0     0 2023-05-08T23:16:07Z 2023-06-06T00:21:36Z 2023-06-06T00:21:31Z MEMBER   0 pydata/xarray/pulls/7830
  • [x] Closes #6836
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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     xarray 13221727 pull
1700678362 PR_kwDOAMm_X85QBdXY 7828 GroupBy: Fix reducing by subset of grouper dims dcherian 2448579 open 0     0 2023-05-08T18:00:54Z 2023-05-10T02:41:39Z   MEMBER   1 pydata/xarray/pulls/7828
  • [x] Tests added

Fixes yet another bug with GroupBy reductions. We weren't assigning the group index when reducing by a subset of dimensions present on the grouper

This will only pass when flox 0.7.1 reaches conda-forge.

 
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     xarray 13221727 pull
1692597701 I_kwDOAMm_X85k4v3F 7808 Default behaviour of `min_count` wrong with flox dcherian 2448579 closed 0     0 2023-05-02T15:04:11Z 2023-05-10T02:39:45Z 2023-05-10T02:39:45Z MEMBER      

What happened?

```python with xr.set_options(display_style="text", use_flox=False): with xr.set_options(use_flox=False): display( xr.DataArray( data=np.array([np.nan, 1, 1, np.nan, 1, 1]), dims="x", coords={"labels": ("x", np.array([1, 2, 3, 1, 2, 3]))}, ) .groupby("labels") .sum() )

with xr.set_options(use_flox=True):
    display(
        xr.DataArray(
            data=np.array([np.nan, 1, 1, np.nan, 1, 1]),
            dims="x",
            coords={"labels": ("x", np.array([1, 2, 3, 1, 2, 3]))},
        )
        .groupby("labels")
        .sum()
    )

```

```

without flox

<xarray.DataArray (labels: 3)> array([0., 2., 2.]) Coordinates: * labels (labels) int64 1 2 3

with flox

<xarray.DataArray (labels: 3)> array([nan, 2., 2.]) Coordinates: * labels (labels) int64 1 2 3 ```

What did you expect to happen?

The same answer. We should set min_count=0 when min_count is None

Minimal Complete Verifiable Example

No response

MVCE confirmation

  • [ ] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • [ ] Complete example — the example is self-contained, including all data and the text of any traceback.
  • [ ] Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • [ ] New issue — a search of GitHub Issues suggests this is not a duplicate.

Relevant log output

No response

Anything else we need to know?

No response

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   completed xarray 13221727 issue
1692612622 PR_kwDOAMm_X85PmMOy 7809 Fix `min_count` behaviour with flox. dcherian 2448579 closed 0     0 2023-05-02T15:13:17Z 2023-05-10T02:39:45Z 2023-05-10T02:39:43Z MEMBER   0 pydata/xarray/pulls/7809
  • [x] Closes #7808
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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     xarray 13221727 pull
1677167290 PR_kwDOAMm_X85Oyokd 7775 [skip-ci] dev whats-new dcherian 2448579 closed 0     0 2023-04-20T17:54:27Z 2023-04-20T21:08:14Z 2023-04-20T21:08:11Z MEMBER   0 pydata/xarray/pulls/7775   
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     xarray 13221727 pull
1677161134 PR_kwDOAMm_X85OynVg 7774 [skip-ci] Release 2023.04.2 dcherian 2448579 closed 0     0 2023-04-20T17:49:46Z 2023-04-20T18:26:39Z 2023-04-20T18:26:37Z MEMBER   0 pydata/xarray/pulls/7774   
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     xarray 13221727 pull
1671616256 PR_kwDOAMm_X85OgCYb 7762 Fix binning by unsorted array dcherian 2448579 closed 0     0 2023-04-17T17:04:45Z 2023-04-18T14:48:28Z 2023-04-18T14:48:23Z MEMBER   0 pydata/xarray/pulls/7762
  • [x] Closes #7759
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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     xarray 13221727 pull
1668569869 PR_kwDOAMm_X85OV_JV 7757 Add whats-new for v2023.04.0 dcherian 2448579 closed 0     0 2023-04-14T16:36:01Z 2023-04-14T17:25:37Z 2023-04-14T17:25:35Z MEMBER   0 pydata/xarray/pulls/7757   
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     xarray 13221727 pull
1658287743 PR_kwDOAMm_X85N0Afw 7736 align: Avoid reindexing when join="exact" dcherian 2448579 closed 0     0 2023-04-07T02:46:08Z 2023-04-12T14:41:53Z 2023-04-12T14:41:51Z MEMBER   0 pydata/xarray/pulls/7736

xref #7730, #7737

 
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     xarray 13221727 pull
1658319105 PR_kwDOAMm_X85N0Gez 7738 [skip-ci] Add alignment benchmarks dcherian 2448579 closed 0     0 2023-04-07T03:40:32Z 2023-04-07T22:31:08Z 2023-04-07T22:31:05Z MEMBER   0 pydata/xarray/pulls/7738

xref #4648

 
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     xarray 13221727 pull
1656619829 PR_kwDOAMm_X85Nuo9M 7729 Test: new index from dask.array computes only once dcherian 2448579 closed 0     0 2023-04-06T03:52:22Z 2023-04-06T04:15:47Z 2023-04-06T04:15:45Z MEMBER   0 pydata/xarray/pulls/7729

Closes #1533

Seems to have been fixed by the indexes refactor

 
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     xarray 13221727 pull
1649611456 I_kwDOAMm_X85iUxLA 7704 follow upstream scipy interpolation improvements dcherian 2448579 open 0     0 2023-03-31T15:46:56Z 2023-03-31T15:46:56Z   MEMBER      

Is your feature request related to a problem?

Scipy 1.10.0 has some great improvements to interpolation (release notes) particularly around the fancier methods like pchip.

It'd be good to see if we can simplify some of our code (or even enable using these options).

Describe the solution you'd like

No response

Describe alternatives you've considered

No response

Additional context

No response

 
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     xarray 13221727 issue
1268667121 PR_kwDOAMm_X845hbaE 6689 Refactor GroupBy init to avoid factorization dcherian 2448579 closed 0     0 2022-06-12T18:41:04Z 2023-03-29T16:28:29Z 2023-03-29T16:28:29Z MEMBER   1 pydata/xarray/pulls/6689

Refactoring GroupBy.__init__ as a step toward #6610

 
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     xarray 13221727 pull
1636110117 PR_kwDOAMm_X85MqTjx 7660 [skip-ci] dev whats-new dcherian 2448579 closed 0     0 2023-03-22T16:22:46Z 2023-03-22T17:57:15Z 2023-03-22T17:57:13Z MEMBER   0 pydata/xarray/pulls/7660   
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     xarray 13221727 pull
1600469223 PR_kwDOAMm_X85Ky0-D 7562 Support first, last with dask arrays dcherian 2448579 closed 0     0 2023-02-27T04:54:09Z 2023-03-03T23:13:57Z 2023-03-03T23:13:52Z MEMBER   0 pydata/xarray/pulls/7562

Use dask.array.reduction. For this we need to add support for the keepdims kwarg to nanfirst and nanlast. Even though the final result is always keepdims=False, dask runs the intermediate steps with keepdims=True.

  • [ ] Closes #xxxx
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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1574631376 PR_kwDOAMm_X85JcpzG 7512 Update HOW_TO_RELEASE.md dcherian 2448579 closed 0     0 2023-02-07T16:23:50Z 2023-02-07T17:40:52Z 2023-02-07T17:40:50Z MEMBER   0 pydata/xarray/pulls/7512   
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1574621206 PR_kwDOAMm_X85Jcnno 7511 Update whats-new for dev dcherian 2448579 closed 0     0 2023-02-07T16:17:20Z 2023-02-07T17:40:28Z 2023-02-07T17:40:26Z MEMBER   0 pydata/xarray/pulls/7511   
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1548082114 PR_kwDOAMm_X85IEVEf 7454 Mention flox in docs dcherian 2448579 closed 0     0 2023-01-18T20:46:30Z 2023-01-26T16:59:44Z 2023-01-26T16:59:41Z MEMBER   0 pydata/xarray/pulls/7454   
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1536791632 PR_kwDOAMm_X85HkDxR 7449 [skip-cii] Add pyodide update instructions to HOW_TO_RELEASE dcherian 2448579 closed 0     0 2023-01-17T17:46:51Z 2023-01-19T14:01:39Z 2023-01-19T14:01:37Z MEMBER   0 pydata/xarray/pulls/7449   
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1548137655 PR_kwDOAMm_X85IEhQU 7455 [skip-ci] whats-new for next release dcherian 2448579 closed 0     0 2023-01-18T21:32:59Z 2023-01-19T14:01:20Z 2023-01-19T14:01:17Z MEMBER   0 pydata/xarray/pulls/7455   
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1473583411 PR_kwDOAMm_X85ELiEY 7351 [skip-ci] whats-new for dev dcherian 2448579 closed 0     0 2022-12-02T23:44:48Z 2022-12-04T18:25:22Z 2022-12-04T18:25:20Z MEMBER   0 pydata/xarray/pulls/7351   
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1472041871 PR_kwDOAMm_X85EGUMF 7345 Whats-new: 2022.12.0 dcherian 2448579 closed 0     0 2022-12-01T22:27:33Z 2022-12-02T22:57:57Z 2022-12-02T22:57:53Z MEMBER   0 pydata/xarray/pulls/7345   
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1436632685 PR_kwDOAMm_X85CPVIi 7257 [skip-ci] dev whats-new dcherian 2448579 closed 0     0 2022-11-04T20:47:21Z 2022-11-04T23:08:03Z 2022-11-04T23:08:01Z MEMBER   0 pydata/xarray/pulls/7257   
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1421036686 PR_kwDOAMm_X85BbOeg 7205 Fix binning when labels are provided. dcherian 2448579 closed 0     0 2022-10-24T15:40:27Z 2022-10-26T15:56:37Z 2022-10-26T15:56:35Z MEMBER   0 pydata/xarray/pulls/7205
  • [x] Closes #7198
  • [x] Tests added
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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802525282 MDExOlB1bGxSZXF1ZXN0NTY4NjUzOTg0 4868 facets and hue with hist dcherian 2448579 open 0     0 2021-02-05T22:49:36Z 2022-10-19T07:27:32Z   MEMBER   0 pydata/xarray/pulls/4868
  • [x] Closes #4288
  • [ ] Tests added
  • [x] Passes pre-commit run --all-files
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
 
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802431534 MDExOlB1bGxSZXF1ZXN0NTY4NTc1NzIw 4866 Refactor line plotting dcherian 2448579 open 0     0 2021-02-05T19:51:24Z 2022-10-18T20:13:14Z   MEMBER   0 pydata/xarray/pulls/4866

Refactors line plotting to use a _plot1d decorator.

Next i'll use this decorator on hist so we can "facet" and "hue" histograms.

see #4288

 
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1408327952 PR_kwDOAMm_X85Aw5A3 7161 dev whats-new dcherian 2448579 closed 0     0 2022-10-13T19:36:19Z 2022-10-18T19:16:22Z 2022-10-13T21:05:08Z MEMBER   0 pydata/xarray/pulls/7161   
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     xarray 13221727 pull
1302718665 PR_kwDOAMm_X847TJVP 6780 Update flox repo URL dcherian 2448579 closed 0     0 2022-07-12T23:25:23Z 2022-10-18T19:16:20Z 2022-07-13T02:36:50Z MEMBER   0 pydata/xarray/pulls/6780   
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1283026595 PR_kwDOAMm_X846Rn-p 6719 Add new datasets to tutorial.load_dataset docstring dcherian 2448579 closed 0     0 2022-06-23T22:20:08Z 2022-10-18T19:16:19Z 2022-06-28T18:53:31Z MEMBER   0 pydata/xarray/pulls/6719   
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1286270270 PR_kwDOAMm_X846cLwN 6732 [skip-ci] Reorganize the Plotting section of API Reference dcherian 2448579 closed 0     0 2022-06-27T19:50:23Z 2022-10-18T19:16:17Z 2022-06-28T18:52:32Z MEMBER   0 pydata/xarray/pulls/6732

One top level heading with Dataset, DataArray, and Faceting subsections.

 
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1302210315 PR_kwDOAMm_X847RabS 6776 Update map_blocks to use chunksizes property. dcherian 2448579 closed 0     0 2022-07-12T15:16:45Z 2022-10-18T19:16:15Z 2022-07-14T17:42:26Z MEMBER   0 pydata/xarray/pulls/6776

Raise nicer error if provided template has no dask arrays.

  • [x] Closes #6763
  • [x] Tests added
 
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1370340170 PR_kwDOAMm_X84-zpR- 7022 Preserve all attrs with GroupBy by default. dcherian 2448579 closed 0     0 2022-09-12T18:26:47Z 2022-10-18T19:15:21Z 2022-09-13T15:30:29Z MEMBER   0 pydata/xarray/pulls/7022

Closes #7012

When use_flox=False, we pass keep_attrs=None to Data*.reduce. This ends up delete Dataset and DataArray level attrs but preserves coordinate variable attrs. We now set the default to True always to match the default behaviour of apply_ufunc used by flox.xarray.xarray_reduce.

  • [x] Closes #7012
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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1330389950 PR_kwDOAMm_X848vgCB 6882 Allow decoding of size-0 datetimes dcherian 2448579 closed 0     0 2022-08-05T21:00:13Z 2022-10-18T19:15:17Z 2022-08-10T17:25:19Z MEMBER   0 pydata/xarray/pulls/6882
  • [x] Closes #1329
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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1306156897 PR_kwDOAMm_X847ejCK 6788 Warn when grouping by dask array. dcherian 2448579 closed 0     0 2022-07-15T15:15:03Z 2022-10-18T19:15:15Z 2022-07-15T18:05:06Z MEMBER   0 pydata/xarray/pulls/6788

Currently computes eagerly; we want to not do that in the future

(broken out from #6689)

 
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1408315481 PR_kwDOAMm_X85Aw2RF 7160 v2022.10.0 whats-new dcherian 2448579 closed 0     0 2022-10-13T19:25:11Z 2022-10-13T20:28:06Z 2022-10-13T20:28:05Z MEMBER   0 pydata/xarray/pulls/7160   
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626591460 MDU6SXNzdWU2MjY1OTE0NjA= 4107 renaming Variable to a dimension name does not convert to IndexVariable dcherian 2448579 closed 0 benbovy 4160723   0 2020-05-28T15:11:49Z 2022-09-27T09:33:42Z 2022-09-27T09:33:42Z MEMBER      

Seen in #4103

MCVE Code Sample

```python from xarray.tests import assert_identical

coord_1 = xr.DataArray([1, 2], dims=["coord_1"], attrs={"attrs": True}) da = xr.DataArray([1, 0], [coord_1]) obj = da.reset_index("coord_1").rename({"coord_1_": "coord_1"}) assert_identical(da, obj) ```

Expected Output

Problem Description

``` AssertionErrorTraceback (most recent call last) <ipython-input-19-02ef6bd89884> in <module> ----> 1 assert_identical(da, obj)

~/work/python/xarray/xarray/tests/init.py in assert_identical(a, b) 160 xarray.testing.assert_identical(a, b) 161 xarray.testing._assert_internal_invariants(a) --> 162 xarray.testing._assert_internal_invariants(b) 163 164

~/work/python/xarray/xarray/testing.py in _assert_internal_invariants(xarray_obj) 265 _assert_variable_invariants(xarray_obj) 266 elif isinstance(xarray_obj, DataArray): --> 267 _assert_dataarray_invariants(xarray_obj) 268 elif isinstance(xarray_obj, Dataset): 269 _assert_dataset_invariants(xarray_obj)

~/work/python/xarray/xarray/testing.py in _assert_dataarray_invariants(da) 210 assert all( 211 isinstance(v, IndexVariable) for (k, v) in da._coords.items() if v.dims == (k,) --> 212 ), {k: type(v) for k, v in da._coords.items()} 213 for k, v in da._coords.items(): 214 _assert_variable_invariants(v, k)

AssertionError: {'coord_1': <class 'xarray.core.variable.Variable'>} ```

Versions

Output of <tt>xr.show_versions()</tt> 
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   completed xarray 13221727 issue
1378174355 I_kwDOAMm_X85SJUWT 7055 Use roundtrip context manager in distributed write tests dcherian 2448579 open 0     0 2022-09-19T15:53:40Z 2022-09-19T15:53:40Z   MEMBER      

What is your issue?

File roundtripping tests in test_distributed.py don't use the roundtrip context manager (thpugh one uses create_tmp_file) so I don't think any created files are being cleaned up.

Example: https://github.com/pydata/xarray/blob/09e467a6a3a8ed68c6c29647ebf2b09288145da1/xarray/tests/test_distributed.py#L91-L119

 
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     xarray 13221727 issue
1262168838 PR_kwDOAMm_X845LyRA 6667 Set keep_attrs for flox dcherian 2448579 closed 0     0 2022-06-06T17:58:10Z 2022-09-12T18:08:35Z 2022-06-06T18:53:37Z MEMBER   0 pydata/xarray/pulls/6667

Closes #6666

False by default following Dataset.reduce

 
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1352462722 PR_kwDOAMm_X8494KNn 6958 [skip-ci] Stop applying topic-documentation label dcherian 2448579 closed 0     0 2022-08-26T16:09:58Z 2022-08-26T16:10:30Z 2022-08-26T16:10:29Z MEMBER   0 pydata/xarray/pulls/6958

Lots of false positives.

 
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1342137214 PR_kwDOAMm_X849V9ip 6925 Update PR labels dcherian 2448579 closed 0     0 2022-08-17T18:38:02Z 2022-08-19T15:53:41Z 2022-08-19T15:53:40Z MEMBER   0 pydata/xarray/pulls/6925

Use topic-documentation and automatically run benchmarks

 
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1326096263 PR_kwDOAMm_X848hKwg 6869 Add cupy-xarray; update pint-xarray url dcherian 2448579 closed 0     0 2022-08-02T16:26:02Z 2022-08-02T16:56:22Z 2022-08-02T16:56:21Z MEMBER   0 pydata/xarray/pulls/6869   
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1313843378 PR_kwDOAMm_X8474tEy 6815 Release notes for v2022.06.0 dcherian 2448579 closed 0     0 2022-07-21T21:51:33Z 2022-07-22T15:45:00Z 2022-07-22T15:44:58Z MEMBER   0 pydata/xarray/pulls/6815
  • [x] Closes #6645
 
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1306166753 PR_kwDOAMm_X847elJQ 6789 Refactor groupby binary ops code. dcherian 2448579 closed 0     0 2022-07-15T15:24:44Z 2022-07-20T01:30:11Z 2022-07-20T01:30:09Z MEMBER   0 pydata/xarray/pulls/6789

Cleaner implementation; also broken out from #6689 

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1306155046 PR_kwDOAMm_X847eipZ 6787 Update groupby attrs tests dcherian 2448579 closed 0     0 2022-07-15T15:13:08Z 2022-07-15T21:37:44Z 2022-07-15T21:37:43Z MEMBER   0 pydata/xarray/pulls/6787

Update tests + add a couple more

 
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1289174987 I_kwDOAMm_X85M1z_L 6739 "center" kwarg ignored when manually iterating over DataArrayRolling dcherian 2448579 closed 0     0 2022-06-29T19:07:07Z 2022-07-14T17:41:01Z 2022-07-14T17:41:01Z MEMBER      

Discussed in https://github.com/pydata/xarray/discussions/6738

<sup>Originally posted by **ckingdon95** June 29, 2022</sup> Hello, I am trying to manually iterate over a DataArrayRolling object, as described [here ](https://docs.xarray.dev/en/stable/user-guide/computation.html#rolling-window-operations)in the documentation. I am confused why the following two code chunks do not produce the same sequence of values. I would like to be able to manually iterate over a DataArrayRolling object, and still be given center-justified windows. Is there a way to do this? ```python import xarray as xr import numpy as np my_data = xr.DataArray(np.arange(1,10), dims="x") # Option 1: take a center-justified rolling average result1 = my_data.rolling(x=3, center=True).mean().values result1 ``` This returns the following values, as expected: ``` array([nan, 2., 3., 4., 5., 6., 7., 8., nan]) ``` Whereas when I do it manually, it is not equivalent: ```python # Option 2: try to manually iterate, but the result is not centered my_data_rolling = my_data.rolling(x=3, center=True) result2 = [window.mean().values.item() for label, window in my_data_rolling] result2 ``` This returns ``` [nan, nan, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0] ``` Is this an issue with the window iterator? If it is not an issue, then is there a way for me to get the center-justified windows in the manual iteration? 
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   completed xarray 13221727 issue

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