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 1442443970,I_kwDOAMm_X85V-fLC,7275,REG: `nc_time_axis` not imported anymore,20629530,closed,0,,,1,2022-11-09T17:02:59Z,2022-11-10T21:45:28Z,2022-11-10T21:45:28Z,CONTRIBUTOR,,,,"### What happened? With xarray 2022.11.0, plotting a DataArray with a `cftime` time axis fails. It fails with a matplotlib error : `TypeError: float() argument must be a string or a real number, not 'cftime._cftime.DatetimeNoLeap'` ### What did you expect to happen? With previous versions of xarray, the `nc_time_axis` package was imported by xarray and these errors were avoided. ### Minimal Complete Verifiable Example ```Python import xarray as xr da = xr.DataArray( list(range(10)), dims=('time',), coords={'time': xr.cftime_range('1900-01-01', periods=10, calendar='noleap', freq='D')} ) da.plot() ``` ### MVCE confirmation - [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [X] Complete example — the example is self-contained, including all data and the text of any traceback. - [X] 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. - [X] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Cell In [1], line 7 1 import xarray as xr 2 da = xr.DataArray( 3 list(range(10)), 4 dims=('time',), 5 coords={'time': xr.cftime_range('1900-01-01', periods=10, calendar='noleap', freq='D')} 6 ) ----> 7 da.plot() File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/xarray/plot/accessor.py:46, in DataArrayPlotAccessor.__call__(self, **kwargs) 44 @functools.wraps(dataarray_plot.plot, assigned=(""__doc__"", ""__annotations__"")) 45 def __call__(self, **kwargs) -> Any: ---> 46 return dataarray_plot.plot(self._da, **kwargs) File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/xarray/plot/dataarray_plot.py:312, in plot(darray, row, col, col_wrap, ax, hue, subplot_kws, **kwargs) 308 plotfunc = hist 310 kwargs[""ax""] = ax --> 312 return plotfunc(darray, **kwargs) File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/xarray/plot/dataarray_plot.py:517, in line(darray, row, col, figsize, aspect, size, ax, hue, x, y, xincrease, yincrease, xscale, yscale, xticks, yticks, xlim, ylim, add_legend, _labels, *args, **kwargs) 513 ylabel = label_from_attrs(yplt, extra=y_suffix) 515 _ensure_plottable(xplt_val, yplt_val) --> 517 primitive = ax.plot(xplt_val, yplt_val, *args, **kwargs) 519 if _labels: 520 if xlabel is not None: File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/matplotlib/axes/_axes.py:1664, in Axes.plot(self, scalex, scaley, data, *args, **kwargs) 1662 lines = [*self._get_lines(*args, data=data, **kwargs)] 1663 for line in lines: -> 1664 self.add_line(line) 1665 if scalex: 1666 self._request_autoscale_view(""x"") File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/matplotlib/axes/_base.py:2340, in _AxesBase.add_line(self, line) 2337 if line.get_clip_path() is None: 2338 line.set_clip_path(self.patch) -> 2340 self._update_line_limits(line) 2341 if not line.get_label(): 2342 line.set_label(f'_child{len(self._children)}') File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/matplotlib/axes/_base.py:2363, in _AxesBase._update_line_limits(self, line) 2359 def _update_line_limits(self, line): 2360 """""" 2361 Figures out the data limit of the given line, updating self.dataLim. 2362 """""" -> 2363 path = line.get_path() 2364 if path.vertices.size == 0: 2365 return File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/matplotlib/lines.py:1031, in Line2D.get_path(self) 1029 """"""Return the `~matplotlib.path.Path` associated with this line."""""" 1030 if self._invalidy or self._invalidx: -> 1031 self.recache() 1032 return self._path File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/matplotlib/lines.py:659, in Line2D.recache(self, always) 657 if always or self._invalidx: 658 xconv = self.convert_xunits(self._xorig) --> 659 x = _to_unmasked_float_array(xconv).ravel() 660 else: 661 x = self._x File ~/mambaforge/envs/xclim/lib/python3.10/site-packages/matplotlib/cbook/__init__.py:1369, in _to_unmasked_float_array(x) 1367 return np.ma.asarray(x, float).filled(np.nan) 1368 else: -> 1369 return np.asarray(x, float) TypeError: float() argument must be a string or a real number, not 'cftime._cftime.DatetimeNoLeap' ``` ### Anything else we need to know? I suspect #7179. This line: https://github.com/pydata/xarray/blob/cc7e09a3507fa342b3790b5c109e700fa12f0b17/xarray/plot/utils.py#L27 does _not_ import `nc_time_axis`. Further down, the variable gets checked and if `False` an error is raised, but if the package still is not imported if `True`. Previously we had: https://github.com/pydata/xarray/blob/fc9026b59d38146a21769cc2d3026a12d58af059/xarray/plot/utils.py#L27-L32 where the package is always imported. Maybe there's a way to import `nc_time_axis` only when needed? ### Environment
INSTALLED VERSIONS ------------------ commit: None python: 3.10.6 | packaged by conda-forge | (main, Aug 22 2022, 20:36:39) [GCC 10.4.0] python-bits: 64 OS: Linux OS-release: 6.0.5-200.fc36.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: fr_CA.UTF-8 LOCALE: ('fr_CA', 'UTF-8') libhdf5: 1.12.2 libnetcdf: 4.8.1 xarray: 2022.11.0 pandas: 1.5.1 numpy: 1.23.4 scipy: 1.8.1 netCDF4: 1.6.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.6.2 nc_time_axis: 1.4.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.5 dask: 2022.10.2 distributed: 2022.10.2 matplotlib: 3.6.2 cartopy: None seaborn: None numbagg: None fsspec: 2022.10.0 cupy: None pint: 0.20.1 sparse: None flox: None numpy_groupies: None setuptools: 65.5.1 pip: 22.3.1 conda: None pytest: 7.2.0 IPython: 8.6.0 sphinx: 5.3.0
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7275/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1242388766,I_kwDOAMm_X85KDVke,6623,Cftime arrays not supported by polyval,20629530,closed,0,,,1,2022-05-19T22:19:14Z,2022-05-31T17:16:04Z,2022-05-31T17:16:04Z,CONTRIBUTOR,,,,"### What happened? I was trying to use polyval with a cftime coordinate and it failed with `TypeError: unsupported operand type(s) for *: 'float' and 'cftime._cftime.DatetimeNoLeap'`. The error seems to originate from #6548, where the process transforming coordinates to numerical values was modified. The new `_ensure_numeric` method seems to ignore the possibility of `cftime` arrays. ### What did you expect to happen? A polynomial to be evaluated along my coordinate. ### Minimal Complete Verifiable Example ```Python import xarray as xr import numpy as np # use_cftime=False will work t = xr.date_range('2001-01-01', periods=100, use_cftime=True, freq='YS') da = xr.DataArray(np.arange(100) ** 3, dims=('time',), coords={'time': t}) coeffs = da.polyfit('time', 4) da2 = xr.polyval(da.time, coeffs).polyfit_coefficients ``` ### MVCE confirmation - [X] Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray. - [X] Complete example — the example is self-contained, including all data and the text of any traceback. - [X] 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. - [X] New issue — a search of GitHub Issues suggests this is not a duplicate. ### Relevant log output ```Python --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Input In [5], in () 2 da = xr.DataArray(np.arange(100) ** 3, dims=('time',), coords={'time': t}) 3 coeffs = da.polyfit('time', 4) ----> 4 da2 = xr.polyval(da.time, coeffs).polyfit_coefficients File ~/Python/xarray/xarray/core/computation.py:1931, in polyval(coord, coeffs, degree_dim) 1929 res = zeros_like(coord) + coeffs.isel({degree_dim: max_deg}, drop=True) 1930 for deg in range(max_deg - 1, -1, -1): -> 1931 res *= coord 1932 res += coeffs.isel({degree_dim: deg}, drop=True) 1934 return res File ~/Python/xarray/xarray/core/_typed_ops.py:103, in DatasetOpsMixin.__imul__(self, other) 102 def __imul__(self, other): --> 103 return self._inplace_binary_op(other, operator.imul) File ~/Python/xarray/xarray/core/dataset.py:6107, in Dataset._inplace_binary_op(self, other, f) 6105 other = other.reindex_like(self, copy=False) 6106 g = ops.inplace_to_noninplace_op(f) -> 6107 ds = self._calculate_binary_op(g, other, inplace=True) 6108 self._replace_with_new_dims( 6109 ds._variables, 6110 ds._coord_names, (...) 6113 inplace=True, 6114 ) 6115 return self File ~/Python/xarray/xarray/core/dataset.py:6154, in Dataset._calculate_binary_op(self, f, other, join, inplace) 6152 else: 6153 other_variable = getattr(other, ""variable"", other) -> 6154 new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars} 6155 ds._variables.update(new_vars) 6156 ds._dims = calculate_dimensions(ds._variables) File ~/Python/xarray/xarray/core/dataset.py:6154, in (.0) 6152 else: 6153 other_variable = getattr(other, ""variable"", other) -> 6154 new_vars = {k: f(self.variables[k], other_variable) for k in self.data_vars} 6155 ds._variables.update(new_vars) 6156 ds._dims = calculate_dimensions(ds._variables) File ~/Python/xarray/xarray/core/_typed_ops.py:402, in VariableOpsMixin.__mul__(self, other) 401 def __mul__(self, other): --> 402 return self._binary_op(other, operator.mul) File ~/Python/xarray/xarray/core/variable.py:2494, in Variable._binary_op(self, other, f, reflexive) 2491 attrs = self._attrs if keep_attrs else None 2492 with np.errstate(all=""ignore""): 2493 new_data = ( -> 2494 f(self_data, other_data) if not reflexive else f(other_data, self_data) 2495 ) 2496 result = Variable(dims, new_data, attrs=attrs) 2497 return result TypeError: unsupported operand type(s) for *: 'float' and 'cftime._cftime.DatetimeGregorian' ``` ### Anything else we need to know? I also noticed that since the Horner PR, `polyfit` and `polyval` do not use the same function to convert coordinates into numerical values. Isn't this dangerous? ### Environment
INSTALLED VERSIONS ------------------ commit: None python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:38:57) [GCC 10.3.0] python-bits: 64 OS: Linux OS-release: 3.10.0-1160.49.1.el7.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: ('en_CA', 'UTF-8') libhdf5: 1.12.1 libnetcdf: 4.8.1 xarray: 2022.3.1.dev267+gd711d58 pandas: 1.4.2 numpy: 1.21.6 scipy: 1.8.0 netCDF4: 1.5.8 pydap: None h5netcdf: None h5py: 3.6.0 Nio: None zarr: 2.11.3 cftime: 1.6.0 nc_time_axis: 1.4.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.4 dask: 2022.04.1 distributed: 2022.4.1 matplotlib: 3.5.1 cartopy: 0.20.2 seaborn: None numbagg: None fsspec: 2022.3.0 cupy: None pint: 0.19.2 sparse: 0.13.0 flox: 0.5.0 numpy_groupies: 0.9.15 setuptools: 62.1.0 pip: 22.0.4 conda: None pytest: None IPython: 8.2.0 sphinx: 4.5.0
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6623/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1175454678,I_kwDOAMm_X85GEAPW,6393, DataArray groupby returning Dataset broken in some cases,20629530,closed,0,,,1,2022-03-21T14:17:25Z,2022-03-21T15:26:20Z,2022-03-21T15:26:20Z,CONTRIBUTOR,,,,"### What happened? This is a the reverse problem of #6379, the `DataArrayGroupBy._combine` method seems broken when the mapped function returns a Dataset (which worked before #5692). ### What did you expect to happen? _No response_ ### Minimal Complete Verifiable Example ```Python import xarray as xr ds = xr.tutorial.open_dataset(""air_temperature"") ds.air.resample(time=""YS"").map(lambda grp: grp.mean(""time"").to_dataset()) ``` ### Relevant log output ```Python --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Input In [3], in ----> 1 ds.air.resample(time=""YS"").map(lambda grp: grp.mean(""time"").to_dataset()) File ~/Python/myxarray/xarray/core/resample.py:223, in DataArrayResample.map(self, func, shortcut, args, **kwargs) 180 """"""Apply a function to each array in the group and concatenate them 181 together into a new array. 182 (...) 219 The result of splitting, applying and combining this array. 220 """""" 221 # TODO: the argument order for Resample doesn't match that for its parent, 222 # GroupBy --> 223 combined = super().map(func, shortcut=shortcut, args=args, **kwargs) 225 # If the aggregation function didn't drop the original resampling 226 # dimension, then we need to do so before we can rename the proxy 227 # dimension we used. 228 if self._dim in combined.coords: File ~/Python/myxarray/xarray/core/groupby.py:835, in DataArrayGroupByBase.map(self, func, shortcut, args, **kwargs) 833 grouped = self._iter_grouped_shortcut() if shortcut else self._iter_grouped() 834 applied = (maybe_wrap_array(arr, func(arr, *args, **kwargs)) for arr in grouped) --> 835 return self._combine(applied, shortcut=shortcut) File ~/Python/myxarray/xarray/core/groupby.py:869, in DataArrayGroupByBase._combine(self, applied, shortcut) 867 index, index_vars = create_default_index_implicit(coord) 868 indexes = {k: index for k in index_vars} --> 869 combined = combined._overwrite_indexes(indexes, coords=index_vars) 870 combined = self._maybe_restore_empty_groups(combined) 871 combined = self._maybe_unstack(combined) TypeError: _overwrite_indexes() got an unexpected keyword argument 'coords' ``` ### Anything else we need to know? I guess the same solution as #6386 could be used! ### Environment
INSTALLED VERSIONS ------------------ commit: None python: 3.9.6 | packaged by conda-forge | (default, Jul 11 2021, 03:39:48) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 5.16.13-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: fr_CA.utf8 LOCALE: ('fr_CA', 'UTF-8') libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 2022.3.1.dev16+g3ead17ea pandas: 1.4.0 numpy: 1.20.3 scipy: 1.7.1 netCDF4: 1.5.7 pydap: None h5netcdf: 0.11.0 h5py: 3.4.0 Nio: None zarr: 2.10.0 cftime: 1.5.0 nc_time_axis: 1.3.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.08.0 distributed: 2021.08.0 matplotlib: 3.4.3 cartopy: None seaborn: None numbagg: None fsspec: 2021.07.0 cupy: None pint: 0.18 sparse: None setuptools: 57.4.0 pip: 21.2.4 conda: None pytest: 6.2.5 IPython: 8.0.1 sphinx: 4.1.2
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6393/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 1173980959,I_kwDOAMm_X85F-Ycf,6379,Dataset groupby returning DataArray broken in some cases,20629530,closed,0,,,1,2022-03-18T20:07:37Z,2022-03-20T18:55:26Z,2022-03-20T18:55:26Z,CONTRIBUTOR,,,,"### What happened? Got a TypeError when resampling a dataset along a dimension, mapping a function to each group. The function returns a DataArray. Failed with : `TypeError: _overwrite_indexes() got an unexpected keyword argument 'variables' ` ### What did you expect to happen? This worked before the merging of #5692. A DataArray was returned as expected. ### Minimal Complete Verifiable Example ```Python import xarray as xr ds = xr.tutorial.open_dataset(""air_temperature"") ds.resample(time=""YS"").map(lambda grp: grp.air.mean(""time"")) ``` ### Relevant log output ```Python --------------------------------------------------------------------------- TypeError Traceback (most recent call last) Input In [37], in ----> 1 ds.resample(time=""YS"").map(lambda grp: grp.air.mean(""time"")) File /opt/miniconda3/envs/xclim-pip/lib/python3.9/site-packages/xarray/core/resample.py:300, in DatasetResample.map(self, func, args, shortcut, **kwargs) 298 # ignore shortcut if set (for now) 299 applied = (func(ds, *args, **kwargs) for ds in self._iter_grouped()) --> 300 combined = self._combine(applied) 302 return combined.rename({self._resample_dim: self._dim}) File /opt/miniconda3/envs/xclim-pip/lib/python3.9/site-packages/xarray/core/groupby.py:999, in DatasetGroupByBase._combine(self, applied) 997 index, index_vars = create_default_index_implicit(coord) 998 indexes = {k: index for k in index_vars} --> 999 combined = combined._overwrite_indexes(indexes, variables=index_vars) 1000 combined = self._maybe_restore_empty_groups(combined) 1001 combined = self._maybe_unstack(combined) TypeError: _overwrite_indexes() got an unexpected keyword argument 'variables' ``` ### Anything else we need to know? In the docstring of `DatasetGroupBy.map` it is not made clear that the passed function should return a dataset, but the opposite is also not said. This worked before and I think the issues comes from #5692, which introduced different signatures for `DataArray._overwrite_indexes` (which is called in my case) and `Dataset._overwrite_indexes` (which is expected by the new `_combine`). If the function passed to `Dataset.resample(...).map` should only return `Dataset`s then I believe a more explicit error is needed, as well as some notice in the docs and a breaking change entry in the changelog. If `DataArray`s should be accepted, then we have a regression here. I may have time to help on this. ### Environment
INSTALLED VERSIONS ------------------ commit: None python: 3.9.6 | packaged by conda-forge | (default, Jul 11 2021, 03:39:48) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 5.16.13-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: fr_CA.utf8 LOCALE: ('fr_CA', 'UTF-8') libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 2022.3.1.dev16+g3ead17ea pandas: 1.4.0 numpy: 1.20.3 scipy: 1.7.1 netCDF4: 1.5.7 pydap: None h5netcdf: 0.11.0 h5py: 3.4.0 Nio: None zarr: 2.10.0 cftime: 1.5.0 nc_time_axis: 1.3.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.08.0 distributed: 2021.08.0 matplotlib: 3.4.3 cartopy: None seaborn: None numbagg: None fsspec: 2021.07.0 cupy: None pint: 0.18 sparse: None setuptools: 57.4.0 pip: 21.2.4 conda: None pytest: 6.2.5 IPython: 8.0.1 sphinx: 4.1.2
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6379/reactions"", ""total_count"": 2, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 1}",,completed,13221727,issue 1173997225,I_kwDOAMm_X85F-cap,6380,Attributes of concatenation coordinate are dropped,20629530,closed,0,,,1,2022-03-18T20:31:17Z,2022-03-20T18:53:46Z,2022-03-20T18:53:46Z,CONTRIBUTOR,,,,"### What happened? When concatenating two objects with `xr.concat` along a new dimension given through a `DataArray`, the attributes of this given coordinate are lost in the concatenation. ### What did you expect to happen? I expected the concatenation coordinate to be identical to the 1D DataArray I gave to `concat`. ### Minimal Complete Verifiable Example ```Python import xarray as xr ds = xr.tutorial.open_dataset(""air_temperature"") concat_dim = xr.DataArray([1, 2], dims=(""condim"",), attrs={""an_attr"": ""yep""}, name=""condim"") out = xr.concat([ds, ds], concat_dim) out.condim.attrs ``` Before #5692, I get: ``` {'an_attr': 'yep'} ``` with the current master, I get: ``` {} ``` ### Anything else we need to know? I'm not 100% sure, but I think the change is due to `xr.core.concat._calc_concat_dim_coord` being replaced by `xr.core.concat.__calc_concat_dim_index`. The former didn't touch the concatenation coordinate, while the latter casts it as an index, thus dropping the attributes in the process. If the solution is to add a check in `xr.concat`, I may have time to implement something simple. ### Environment
INSTALLED VERSIONS ------------------ commit: None python: 3.9.6 | packaged by conda-forge | (default, Jul 11 2021, 03:39:48) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 5.16.13-arch1-1 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: fr_CA.utf8 LOCALE: ('fr_CA', 'UTF-8') libhdf5: 1.12.0 libnetcdf: 4.7.4 xarray: 2022.3.1.dev16+g3ead17ea pandas: 1.4.0 numpy: 1.20.3 scipy: 1.7.1 netCDF4: 1.5.7 pydap: None h5netcdf: 0.11.0 h5py: 3.4.0 Nio: None zarr: 2.10.0 cftime: 1.5.0 nc_time_axis: 1.3.1 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.08.0 distributed: 2021.08.0 matplotlib: 3.4.3 cartopy: None seaborn: None numbagg: None fsspec: 2021.07.0 cupy: None pint: 0.18 sparse: None setuptools: 57.4.0 pip: 21.2.4 conda: None pytest: 6.2.5 IPython: 8.0.1 sphinx: 4.1.2
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6380/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 635542241,MDExOlB1bGxSZXF1ZXN0NDMxODg5NjQ0,4135,Correct dask handling for 1D idxmax/min on ND data,20629530,closed,0,,,1,2020-06-09T15:36:09Z,2020-06-25T16:09:59Z,2020-06-25T03:59:52Z,CONTRIBUTOR,,0,pydata/xarray/pulls/4135," - [x] Closes #4123 - [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 Based on comments on dask/dask#3096, I fixed the dask indexing error that occurred when `idxmax/idxmin` were called on ND data (where N > 2). Added tests are very simplistic, I believe the 1D and 2D tests already cover most cases, I just wanted to test that is was indeed working on ND data, assuming that non-dask data was already treated properly. I believe this doesn't conflict with #3936.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4135/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull