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,2448579,open,0,,,0,2024-05-03T22:21:44Z,2024-05-03T22:23:34Z,,MEMBER,,1,pydata/xarray/pulls/8998,Builds on #8997 ,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8998/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2187743087,PR_kwDOAMm_X85ptH1f,8840,"Grouper, Resampler as public api",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` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8840/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2228319306,I_kwDOAMm_X86E0XRK,8914,swap_dims does not propagate indexes properly,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](https://mybinder.org/v2/gh/pydata/xarray/main?urlpath=lab/tree/doc/examples/blank_template.ipynb), 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
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8914/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 2021856935,PR_kwDOAMm_X85g81gb,8509,Proof of concept - public Grouper objects,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() ```","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8509/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 2052952379,I_kwDOAMm_X856XZE7,8568,Raise when assigning attrs to virtual variables (default coordinate arrays),2448579,open,0,,,0,2023-12-21T19:24:11Z,2023-12-21T19:24:19Z,,MEMBER,,,,"### Discussed in https://github.com/pydata/xarray/discussions/8567
Originally posted by **matthew-brett** December 21, 2023 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.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8568/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1954809370,I_kwDOAMm_X850hAYa,8353,Update benchmark suite for asv 0.6.1,2448579,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. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8353/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1975400777,PR_kwDOAMm_X85efqSl,8408,Generalize explicit_indexing_adapter,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`,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8408/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1942893480,I_kwDOAMm_X85zzjOo,8306,keep_attrs for NamedArray,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.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8306/reactions"", ""total_count"": 4, ""+1"": 4, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1902086612,PR_kwDOAMm_X85aoYuf,8206,flox: Set fill_value=np.nan always.,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` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8206/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1888576440,I_kwDOAMm_X85wkWO4,8162,Update group by multi index,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_ ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8162/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1824824446,I_kwDOAMm_X85sxJx-,8025,"Support Groupby first, last with flox",2448579,open,0,,,0,2023-07-27T17:07:51Z,2023-07-27T19:08:06Z,,MEMBER,,,,"### Is your feature request related to a problem? [flox](https://github.com/xarray-contrib/flox) recently added support for first, last, nanfirst, nanlast. So we should support that on the Xarray GroupBy object. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/8025/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1700678362,PR_kwDOAMm_X85QBdXY,7828,GroupBy: Fix reducing by subset of grouper dims,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. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7828/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1649611456,I_kwDOAMm_X85iUxLA,7704,follow upstream scipy interpolation improvements,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](https://docs.scipy.org/doc/scipy/release.1.10.0.html#scipy-interpolate-improvements)) 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_","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7704/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 802525282,MDExOlB1bGxSZXF1ZXN0NTY4NjUzOTg0,4868,facets and hue with hist,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` ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4868/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 802431534,MDExOlB1bGxSZXF1ZXN0NTY4NTc1NzIw,4866,Refactor line plotting,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 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4866/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 1378174355,I_kwDOAMm_X85SJUWT,7055,Use roundtrip context manager in distributed write tests,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","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7055/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1203414243,I_kwDOAMm_X85HuqTj,6481,refactor broadcast for flexible indexes,2448579,open,0,,,0,2022-04-13T14:51:19Z,2022-04-13T14:51:28Z,,MEMBER,,,,"### What is your issue? From @benbovy in https://github.com/pydata/xarray/pull/6477 > - extract common indexes and explicitly pass them to the Dataset and DataArray constructors (when implemented) that are called in the broadcast helper functions (there are some temporary and ugly hacks in create_default_index_implicit so that it works now with pandas multi-indexes wrapped in coordinate variables without the need to pass those indexes explicitly) > - extract common indexes based on the dimension(s) of their coordinates and not their name (e.g., case of non-dimension but indexed coordinate) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6481/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1194790343,I_kwDOAMm_X85HNw3H,6445,map removes non-dimensional coordinate variables,2448579,open,0,,,0,2022-04-06T15:40:40Z,2022-04-06T15:40:40Z,,MEMBER,,,,"### What happened? ``` python ds = xr.Dataset( {""a"": (""x"", [1, 2, 3])}, coords={""c"": (""x"", [1, 2, 3]), ""d"": (""y"", [1, 2, 3, 4])} ) print(ds.coords) mapped = ds.map(lambda x: x) print(mapped.coords) ``` Variables `d` gets dropped in the `map` call. It does not share any dimensions with any of the data variables. ``` Coordinates: c (x) int64 1 2 3 d (y) int64 1 2 3 4 Coordinates: c (x) int64 1 2 3 ``` ### What did you expect to happen? _No response_ ### Minimal Complete Verifiable Example _No response_ ### Relevant log output _No response_ ### Anything else we need to know? _No response_ ### Environment xarray 2022.03.0","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6445/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1171916710,I_kwDOAMm_X85F2gem,6372,"apply_ufunc + dask=""parallelized"" + no core dimensions should raise a nicer error about core dimensions being absent",2448579,open,0,,,0,2022-03-17T04:25:37Z,2022-03-17T05:10:16Z,,MEMBER,,,,"### What happened? From https://github.com/pydata/xarray/discussions/6370 Calling `apply_ufunc(..., dask=""parallelized"")` with no core dimensions and dask input ""works"" but raises an error on compute (`ValueError: axes don't match array` from `np.transpose`). ``` python xr.apply_ufunc( lambda x: np.mean(x), dt, dask=""parallelized"" ) ``` ### What did you expect to happen? With numpy data the apply_ufunc call does raise an error: ``` xr.apply_ufunc( lambda x: np.mean(x), dt.compute(), dask=""parallelized"" ) ``` ``` ValueError: applied function returned data with unexpected number of dimensions. Received 0 dimension(s) but expected 1 dimensions with names: ('x',) ``` ### Minimal Complete Verifiable Example ``` python import xarray as xr dt = xr.Dataset( data_vars=dict( value=([""x""], [1,1,2,2,2,3,3,3,3,3]), ), coords=dict( lon=([""x""], np.linspace(0,1,10)), ), ).chunk(chunks={'x': tuple([2,3,5])}) # three chunks of different size xr.apply_ufunc( lambda x: np.mean(x), dt, dask=""parallelized"" ) ``` ### Relevant log output _No response_ ### Anything else we need to know? _No response_ ### Environment N/A","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6372/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1048856436,I_kwDOAMm_X84-hEd0,5962,Test resampling with dask arrays,2448579,open,0,,,0,2021-11-09T17:02:45Z,2021-11-09T17:02:45Z,,MEMBER,,,,"I noticed that we don't test resampling with dask arrays (well just one). This could be a good opportunity to convert `test_groupby.py` to use test fixtures like in https://github.com/pydata/xarray/pull/5411 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5962/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 1043846371,I_kwDOAMm_X84-N9Tj,5934,add test for custom backend entrypoint,2448579,open,0,,,0,2021-11-03T16:57:14Z,2021-11-03T16:57:21Z,,MEMBER,,,,"From https://github.com/pydata/xarray/pull/5931 It would be good to add a test checking that custom backend entrypoints work. This might involve creating a dummy package that registers an entrypoint (https://github.com/pydata/xarray/pull/5931#issuecomment-959131968) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5934/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 938141608,MDU6SXNzdWU5MzgxNDE2MDg=,5582,Faster unstacking of dask arrays,2448579,open,0,,,0,2021-07-06T18:12:05Z,2021-07-06T18:54:40Z,,MEMBER,,,,"Recent dask version support assigning to a list of ints along one dimension. we can use this for unstacking (diff builds on #5577) ```diff diff --git i/xarray/core/variable.py w/xarray/core/variable.py index 222e8dab9..a50dfc574 100644 --- i/xarray/core/variable.py +++ w/xarray/core/variable.py @@ -1593,11 +1593,9 @@ class Variable(AbstractArray, NdimSizeLenMixin, VariableArithmetic): else: dtype = self.dtype - if sparse: + if sparse and not is_duck_dask_array(reordered): # unstacking a dense multitindexed array to a sparse array - # Use the sparse.COO constructor until sparse supports advanced indexing - # https://github.com/pydata/sparse/issues/114 - # TODO: how do we allow different sparse array types + # Use the sparse.COO constructor since we cannot assign to sparse.COO from sparse import COO codes = zip(*index.codes) @@ -1618,19 +1616,23 @@ class Variable(AbstractArray, NdimSizeLenMixin, VariableArithmetic): ) else: + # dask supports assigning to a list of ints along one axis only. + # So we construct an array with the last dimension flattened, + # assign the values, then reshape to the final shape. + intermediate_shape = reordered.shape[:-1] + (np.prod(new_dim_sizes),) + indexer = np.ravel_multi_index(index.codes, new_dim_sizes) data = np.full_like( self.data, fill_value=fill_value, - shape=new_shape, + shape=intermediate_shape, dtype=dtype, ) # Indexer is a list of lists of locations. Each list is the locations # on the new dimension. This is robust to the data being sparse; in that # case the destinations will be NaN / zero. - # sparse doesn't support item assigment, - # https://github.com/pydata/sparse/issues/114 - data[(..., *indexer)] = reordered + data[(..., indexer)] = reordered + data = data.reshape(new_shape) return self._replace(dims=new_dims, data=data) ``` This should be what `alignment.reindex_variables` is doing but I don't fully understand that function. The annoying bit is figuring out when to use this version and what to do with things like dask wrapping sparse. I think we want to loop over each variable in `Dataset.unstack` calling `Variable.unstack` and dispatch based on the type of `Variable.data` to easily handle all the edge cases. cc @Illviljan if you're interested in implementing this","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5582/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 798586325,MDU6SXNzdWU3OTg1ODYzMjU=,4852,mention HDF files in docs,2448579,open,0,,,0,2021-02-01T18:05:23Z,2021-07-04T01:24:22Z,,MEMBER,,,,"This is such a common question that we should address it in the docs. Just saying that some hdf5 files can be opened with `h5netcdf`, and that the user needs to manually create xarray objects with everything else should be enough. https://xarray.pydata.org/en/stable/io.html","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4852/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 797053785,MDU6SXNzdWU3OTcwNTM3ODU=,4848,simplify API reference presentation,2448579,open,0,,,0,2021-01-29T17:23:41Z,2021-01-29T17:23:46Z,,MEMBER,,,,"Can we remove `xarray.core.rolling` and `core.rolling` on the left and right respectively? I think the API reference would be a lot more readable if we could do that ![image](https://user-images.githubusercontent.com/2448579/106306900-e7f27e00-621b-11eb-8ddd-2b9c15abdfca.png) ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4848/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 787486472,MDU6SXNzdWU3ODc0ODY0NzI=,4817,Add encoding to HTML repr,2448579,open,0,,,0,2021-01-16T15:14:50Z,2021-01-24T17:31:31Z,,MEMBER,,,," **Is your feature request related to a problem? Please describe.** `.encoding` is somewhat hidden since we don't show it in a repr. **Describe the solution you'd like** I think it'd be nice to add it to the HTML repr, collapsed by default. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4817/reactions"", ""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 648250671,MDU6SXNzdWU2NDgyNTA2NzE=,4189,List supported options for `backend_kwargs` in `open_dataset`,2448579,open,0,,,0,2020-06-30T15:01:31Z,2020-12-15T04:28:04Z,,MEMBER,,,,"We should list supported options for `backend_kwargs` in the docstring for `open_dataset`and possibly in `io.rst` xref #4187 ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4189/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 538521723,MDU6SXNzdWU1Mzg1MjE3MjM=,3630,reviewnb for example notebooks?,2448579,open,0,,,0,2019-12-16T16:34:28Z,2019-12-16T16:34:28Z,,MEMBER,,,,"What do people think of adding ReviewNB https://www.reviewnb.com/ to facilitate easy reviewing of example notebooks? ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3630/reactions"", ""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue 435787982,MDU6SXNzdWU0MzU3ODc5ODI=,2913,Document xarray data model,2448579,open,0,,,0,2019-04-22T16:23:41Z,2019-04-22T16:23:41Z,,MEMBER,,,,It would be nice to have a separate page that detailed this for users unfamiliar with netCDF. ,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2913/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue