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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
1655786395 PR_kwDOAMm_X85Nr4We 7725 [DOC] resample and then apply func on time+other variables pierreloicq 8809578 closed 0     0 2023-04-05T14:54:45Z 2023-04-06T07:13:58Z 2023-04-06T02:15:01Z CONTRIBUTOR   0 pydata/xarray/pulls/7725

It cannot be run with python since previous dataset is unidimensionnal. Feel free to make it more rigorous if you want. 

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     xarray 13221727 pull
1559907732 PR_kwDOAMm_X85Ir0Y_ 7481 clarification for thresh arg of dataset.dropna() pierreloicq 8809578 closed 0     3 2023-01-27T15:00:34Z 2023-02-14T13:57:38Z 2023-02-14T13:57:37Z CONTRIBUTOR   0 pydata/xarray/pulls/7481   
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     xarray 13221727 pull
1522867648 PR_kwDOAMm_X85G1cXE 7425 groupby in resample doc and vice-versa pierreloicq 8809578 closed 0     0 2023-01-06T16:54:32Z 2023-01-09T09:43:41Z 2023-01-06T18:25:02Z CONTRIBUTOR   0 pydata/xarray/pulls/7425

Since groupby is a bit like resample on non contiguous data

 
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1030492705 PR_kwDOAMm_X84tZNhC 5876 _season_from_months can now handle np.nan pierreloicq 8809578 closed 0     15 2021-10-19T16:04:41Z 2023-01-06T16:59:18Z 2022-01-11T16:06:18Z CONTRIBUTOR   0 pydata/xarray/pulls/5876

_season_from_months can now handle np.nan and values outside of [1,12]

I passed these tests:

``` def test_season(): months = np.array([ 1, 2, 3, 4, 5, np.nan]) assert ( _season_from_months(months) == np.array(['DJF', 'DJF', 'MAM', 'MAM', 'MAM', 'na']) ).all()

months = np.array([ 1, 100, 3, 13, 0, -5])
assert ( _season_from_months(months) == np.array(['DJF', 'na', 'MAM', 'na', 'na', 'na']) ).all()

months = np.array(range(1, 13))
assert ( _season_from_months(months) == np.array(['DJF', 'DJF', 'MAM', 'MAM', 'MAM', 'JJA', 'JJA', 'JJA', 'SON', 'SON', 'SON', 'DJF']) ).all()

test_season() ```

 
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     xarray 13221727 pull
1425890688 PR_kwDOAMm_X85BrgOp 7231 assign_coords docs: see also Dataset.set_coords pierreloicq 8809578 closed 0     1 2022-10-27T16:06:19Z 2022-10-28T07:15:03Z 2022-10-27T17:07:28Z CONTRIBUTOR   0 pydata/xarray/pulls/7231   
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     xarray 13221727 pull
1425890470 PR_kwDOAMm_X85BrgLj 7230 set_coords docs: see also Dataset.assign_coords pierreloicq 8809578 closed 0     1 2022-10-27T16:06:08Z 2022-10-28T07:14:42Z 2022-10-27T17:08:30Z CONTRIBUTOR   0 pydata/xarray/pulls/7230   
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     xarray 13221727 pull
1424095149 PR_kwDOAMm_X85BlcxY 7226 make clearer that sortby() do not run inplace pierreloicq 8809578 closed 0     1 2022-10-26T14:06:23Z 2022-10-26T15:56:02Z 2022-10-26T15:56:02Z CONTRIBUTOR   0 pydata/xarray/pulls/7226

...as python List sort() is in-place

 
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     xarray 13221727 pull

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