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| id ▼ | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 262983973 | MDExOlB1bGxSZXF1ZXN0MjYyOTgzOTcz | 2828 | closed | 0 | Add quantile method to GroupBy | huard 81219 | - [x] Tests added - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Fixes #3018 Note that I've added an unrelated test that exposes an issue with grouping when there is only one element per group. | 2019-03-20T18:20:41Z | 2019-06-24T15:21:36Z | 2019-06-24T15:21:29Z | 2019-06-24T15:21:28Z | b054c317f86639cd3b889a96d77ddb3798f8584e | 0 | f71d05e1275ad3308f608d9f2476352bcf7d68a6 | 223a05f1b77d4efe8ac7d4dc2c24bff61335693c | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/2828 | ||||
| 317054253 | MDExOlB1bGxSZXF1ZXN0MzE3MDU0MjUz | 3305 | closed | 0 | Honor `keep_attrs` in DataArray.quantile | huard 81219 | <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #3304 - [x] Tests added - [x] Passes `black . && mypy . && flake8` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Note that I've set the default to True (if keep_attrs is None). This sounded reasonable since quantiles share the same units and properties as the original array, but I can switch it to False if that's the usual default. | 2019-09-12T19:27:14Z | 2019-09-15T22:16:27Z | 2019-09-15T22:16:15Z | 2019-09-15T22:16:15Z | b65ce8666020ba3a0300154655d2e5c05884d73b | 0 | f4552adc2f9c21cd58d6bdee7eb29f7d0f1d6bd3 | 69c7e01e5167a3137c285cb50d1978252bb8bcbf | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/3305 | ||||
| 353735038 | MDExOlB1bGxSZXF1ZXN0MzUzNzM1MDM4 | 3631 | closed | 0 | Add support for CFTimeIndex in get_clean_interp_index | huard 81219 | <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #3641 - [x] Tests added - [x] Passes `black . && mypy . && flake8` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Related to #3349 As suggested by @spencerkclark, index values are computed as a delta with respect to 1970-01-01. At the moment, this fails if dates fall outside of the range for nanoseconds timedeltas [ 1678 AD, 2262 AD]. Is this something we can fix ? | 2019-12-16T19:57:24Z | 2020-01-26T18:36:24Z | 2020-01-26T14:10:37Z | 2020-01-26T14:10:37Z | 8772355b23e2a451697023844a0e6b688e1468e1 | 0 | 6f0c5042c955ba26adceaa6fb3c1db665204ca38 | c32e58b4fff72816c6b554db51509bea6a891cdc | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/3631 | ||||
| 354730729 | MDExOlB1bGxSZXF1ZXN0MzU0NzMwNzI5 | 3642 | closed | 0 | Make datetime_to_numeric more robust to overflow errors | huard 81219 | <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #3641 - [x] Tests added - [x] Passes `black . && mypy . && flake8` - [ ] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API This is likely only safe with NumPy>=1.17 though. | 2019-12-18T17:34:41Z | 2020-01-20T19:21:49Z | 2020-01-20T19:21:49Z | 3c29b173ddcb98673387c0e41bf8308d98f0cc10 | 0 | 49641632ac4c13f53ff5499d0bc583690ad70f4d | 3cbc459caa010f9b5042d3fa312b66c9b2b6c403 | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/3642 | |||||
| 372062536 | MDExOlB1bGxSZXF1ZXN0MzcyMDYyNTM2 | 3758 | closed | 0 | Fix interp bug when indexer shares coordinates with array | huard 81219 | <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #3252 - [x] Tests added - [x] Passes `isort -rc . && black . && mypy . && flake8` - [x] Fully documented, including `whats-new.rst` for all changes and `api.rst` for new API Replaces #3262 (I think). | 2020-02-06T19:06:22Z | 2020-03-13T13:58:38Z | 2020-03-13T13:58:38Z | 2020-03-13T13:58:38Z | 0d95ebac19faa3af25ac369d1e8177535022c0d9 | 0 | 7042803da07f06d3877cfa2599fa06685db14a83 | 8512b7bf498c0c300f146447c0b05545842e9404 | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/3758 | ||||
| 519474743 | MDExOlB1bGxSZXF1ZXN0NTE5NDc0NzQz | 4573 | closed | 0 | Update xESMF link to pangeo-xesmf in related-projects | huard 81219 | <!-- Feel free to remove check-list items aren't relevant to your change --> The new link is where development now occurs. | 2020-11-11T22:00:34Z | 2020-11-12T14:54:08Z | 2020-11-12T14:53:56Z | 2020-11-12T14:53:56Z | 76036bd239ad2fbf7aa6948ab61a6215c22c3d6e | 0 | 5d5866898eccf1a14e26fd58b7d2f228e2d2d07b | e71c7b4ea967c32fa1c9fd99209a0d4cc05e1577 | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/4573 | ||||
| 1766894598 | PR_kwDOAMm_X85pUKwG | 8821 | open | 0 | Add small test exposing issue from #7794 and suggestion for `_wrap_numpy_scalars` fix | huard 81219 | `_wrap_numpy_scalars` relies on `np.isscalar`, which incorrectly labels a single cftime object as not a scalar. ```python import cftime import numpy as np c = cftime.datetime(2000, 1, 1, calendar='360_day') np.isscalar(c) # False ``` The PR adds logic to handle non-numpy objects using the `np.ndim` function. The logic for built-ins and numpy objects should remain the same. The function logic could possibly be rewritten more clearly as ```python if hasattr(array, "dtype"): if np.isscalar(array): return np.array(array) else: return array if np.ndim(array) == 0: return np.array(array) return array ``` <!-- Feel free to remove check-list items aren't relevant to your change --> - [x] Closes #7794 - [x] Tests added - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` - [ ] New functions/methods are listed in `api.rst` | 2024-03-11T23:40:17Z | 2024-04-03T18:53:28Z | 06dd0ddbac632b48a45e2b933153a16cbba318e0 | 0 | 12217501029657ba8b6e90a4243bbe45dd73a228 | 90e00f0022c8d1871f441470d08c79bb3b03c164 | CONTRIBUTOR | xarray 13221727 | https://github.com/pydata/xarray/pull/8821 |
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