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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
1806239984 PR_kwDOAMm_X85Vl5Ch 7989 Allow opening datasets with nD dimenson coordinate variables. dcherian 2448579 closed 0     5 2023-07-15T17:33:18Z 2023-07-19T19:06:25Z 2023-07-19T18:25:33Z MEMBER   0 pydata/xarray/pulls/7989
  • [x] Closes #2233
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

Avoid automatic creating of Index variable when nD variable shares name with one of its dimensions.

Closes #2233

```python url = "http://www.smast.umassd.edu:8080/thredds/dodsC/FVCOM/NECOFS/Forecasts/NECOFS_GOM3_FORECAST.nc" ds = xr.open_dataset(url, engine="netcdf4") display(ds)

xr.testing._assert_internal_invariants(ds, check_default_indexes=False) ! no raise on #7368 ```

~The internal invariants assert fails on main but succeeds on #7368~. EDIT: now fixed the invariants check.

 
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     xarray 13221727 pull
1639732867 PR_kwDOAMm_X85M2fjy 7670 Delete built-in cfgrib backend dcherian 2448579 closed 0     5 2023-03-24T16:53:56Z 2023-06-01T15:22:33Z 2023-03-29T15:19:51Z MEMBER   0 pydata/xarray/pulls/7670
  • [x] Closes #7199
  • [x] Tests ~added~ deleted
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst
 
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1284071791 PR_kwDOAMm_X846VIdv 6721 Fix .chunks loading lazy backed array data dcherian 2448579 closed 0     5 2022-06-24T18:45:45Z 2022-06-29T20:15:16Z 2022-06-29T20:06:36Z MEMBER   0 pydata/xarray/pulls/6721
  • [x] Closes #6538
  • [x] Tests added
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

@shoyer is there a way to test this?

 
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517855271 MDExOlB1bGxSZXF1ZXN0MzM2ODQ0OTE1 3487 Respect user-specified coordinates attribute. dcherian 2448579 closed 0     5 2019-11-05T15:46:00Z 2019-12-10T16:02:20Z 2019-12-10T16:02:01Z MEMBER   0 pydata/xarray/pulls/3487

A minimally invasive solution to #3351. If variable.encoding["coordinates"] is specified, we write that attribute to disk and warn the user that roundtripping may not work.

  • [x] Closes #3351
  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API
 
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511668854 MDExOlB1bGxSZXF1ZXN0MzMxODIzODAw 3441 fix plotting with transposed nondim coords. dcherian 2448579 closed 0     5 2019-10-24T02:42:18Z 2019-12-04T21:37:03Z 2019-12-04T16:45:13Z MEMBER   0 pydata/xarray/pulls/3441
  • [x] Closes #3138
  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API
 
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520252049 MDExOlB1bGxSZXF1ZXN0MzM4ODczODg3 3500 make coarsen reductions consistent with reductions on other classes dcherian 2448579 closed 0     5 2019-11-08T21:56:03Z 2019-12-04T16:11:21Z 2019-12-04T16:11:16Z MEMBER   0 pydata/xarray/pulls/3500
  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

This PR uses inject_reduce_methods to inject reduction methods into the Coarsen classes. So now we can do coarsen.count() and pass skipna down to the reduction methods.

 
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439418506 MDExOlB1bGxSZXF1ZXN0Mjc1MjI4MzM3 2935 plot: If provided with colormap do not modify it. dcherian 2448579 closed 0     5 2019-05-02T04:00:43Z 2019-05-09T16:19:57Z 2019-05-09T16:19:53Z MEMBER   0 pydata/xarray/pulls/2935
  • [x] Closes #2932
  • [x] Tests added
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

If provided a Colormap we don't override it anymore. facetgrid determines a colormap first and passes that down, so this prevents overwriting.

 
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279595497 MDExOlB1bGxSZXF1ZXN0MTU2NjIwNjM4 1762 ENH: Add dt.date accessor. dcherian 2448579 closed 0     5 2017-12-06T01:43:51Z 2018-05-10T05:12:15Z 2018-01-14T00:28:11Z MEMBER   0 pydata/xarray/pulls/1762

This PR lets us access dt.date thereby removing all higher frequency time information.

Use case: Just like dayofyear but easier to interpret when only looking at 1 year of data.

Example: Start with da.time <xarray.DataArray 'time' (time: 8737)> array(['2014-01-01T00:00:00.000000000', '2014-01-01T01:00:00.000000000', '2014-01-01T02:00:00.000000000', ..., '2014-12-30T22:00:00.000000000', '2014-12-30T23:00:00.000000000', '2014-12-31T00:00:00.000000000'], dtype='datetime64[ns]') Coordinates: * time (time) datetime64[ns] 2014-01-01 2014-01-01T01:00:00 ...

then da.time.dt.date yields <xarray.DataArray 'date' (time: 8737)> array(['2014-01-01T00:00:00.000000000', '2014-01-01T00:00:00.000000000', '2014-01-01T00:00:00.000000000', ..., '2014-12-30T00:00:00.000000000', '2014-12-30T00:00:00.000000000', '2014-12-31T00:00:00.000000000'], dtype='datetime64[ns]') Coordinates: * time (time) datetime64[ns] 2014-01-01 2014-01-01T01:00:00 ...

  • [x] Tests added (for all bug fixes or enhancements)
  • [x] Tests passed (for all non-documentation changes)
  • [x] Passes git diff upstream/master **/*py | flake8 --diff (remove if you did not edit any Python files)
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)
 
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     xarray 13221727 pull

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