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 1461935127,I_kwDOAMm_X85XI1wX,7314,Scatter plot infers weird default values,81219,closed,0,,,2,2022-11-23T15:10:41Z,2023-02-11T20:55:17Z,2023-02-11T20:55:17Z,CONTRIBUTOR,,,,"### What happened? The `xarray.plot.scatter` method has changed its behavior in 2022.10.0. Code that used to work now doesn't. The issue seems to be related to default values for the size and hue of markers. Instead of using `s` and `c` arguments, xarray tries to infer DataArrays to use, but picks non-sensical values. ### What did you expect to happen? A scatter plot with default size and color for markers. Now xarray has inferred that the size is somehow related to the `j` dimension, and the hue to `bnds`. Note that the calculations required to draw the figure with those defaults take a huge amount of time. In the example below, I've subsetted the file so the code runs in a short time. Without subsetting, it runs forever. ### Minimal Complete Verifiable Example ```Python import xarray as xr from matplotlib import pyplot as plt url = ""https://pavics.ouranos.ca/twitcher/ows/proxy/thredds/dodsC/birdhouse/testdata/xclim/cmip6/sic_SImon_CCCma-CanESM5_ssp245_r13i1p2f1_2020.nc"" ds = xr.open_dataset(url) t = ds.isel(i=slice(0,10), j=slice(0,11)) t.plot.scatter(x=""longitude"", y=""latitude"", s=1) plt.show() ``` ### 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 _No response_ ### Anything else we need to know? ![image](https://user-images.githubusercontent.com/81219/203580544-d042a859-11a7-4b48-9878-3a43c5359b3a.png) ### Environment
INSTALLED VERSIONS ------------------ commit: None python: 3.10.4 | packaged by conda-forge | (main, Mar 24 2022, 17:39:04) [GCC 10.3.0] python-bits: 64 OS: Linux OS-release: 5.4.0-131-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: ('en_CA', 'UTF-8') libhdf5: 1.10.4 libnetcdf: 4.7.3 xarray: 2022.10.0 pandas: 1.4.3 numpy: 1.21.4 scipy: None netCDF4: 1.5.7 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.5.1.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.5 dask: 2022.7.0 distributed: None matplotlib: 3.6.2 cartopy: None seaborn: None numbagg: None fsspec: 2022.5.0 cupy: None pint: 0.20.1 sparse: None flox: None numpy_groupies: None setuptools: 62.6.0 pip: 22.0.4 conda: None pytest: 7.1.2
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7314/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 937160239,MDU6SXNzdWU5MzcxNjAyMzk=,5576,Slicing bug with pandas 1.3 and CFTimeIndex,81219,closed,0,,,2,2021-07-05T14:44:17Z,2021-07-05T16:50:30Z,2021-07-05T16:50:30Z,CONTRIBUTOR,,,," **What happened**: Slicing into a DataArray along time with a CFTimeIndex fails since upgrade to pandas 1.3 **What you expected to happen**: The usual. **Minimal Complete Verifiable Example**: ```python import xarray as xr t = xr.cftime_range('2000-01-01', '2030-12-31', freq='D', calendar='noleap') ref = xr.DataArray(range(len(t)), dims=('time',), coords={'time': t}) ref.sel(time=slice(None, ""2015-01-01"")) ``` ```python --------------------------------------------------------------------------- TypeError Traceback (most recent call last) in ----> 1 ref.sel(time=slice(None, ""2015-01-01"")) ~/.conda/envs/xclim/lib/python3.8/site-packages/xarray/core/dataarray.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs) 1269 Dimensions without coordinates: points 1270 """""" -> 1271 ds = self._to_temp_dataset().sel( 1272 indexers=indexers, 1273 drop=drop, ~/.conda/envs/xclim/lib/python3.8/site-packages/xarray/core/dataset.py in sel(self, indexers, method, tolerance, drop, **indexers_kwargs) 2363 """""" 2364 indexers = either_dict_or_kwargs(indexers, indexers_kwargs, ""sel"") -> 2365 pos_indexers, new_indexes = remap_label_indexers( 2366 self, indexers=indexers, method=method, tolerance=tolerance 2367 ) ~/.conda/envs/xclim/lib/python3.8/site-packages/xarray/core/coordinates.py in remap_label_indexers(obj, indexers, method, tolerance, **indexers_kwargs) 419 } 420 --> 421 pos_indexers, new_indexes = indexing.remap_label_indexers( 422 obj, v_indexers, method=method, tolerance=tolerance 423 ) ~/.conda/envs/xclim/lib/python3.8/site-packages/xarray/core/indexing.py in remap_label_indexers(data_obj, indexers, method, tolerance) 272 coords_dtype = data_obj.coords[dim].dtype 273 label = maybe_cast_to_coords_dtype(label, coords_dtype) --> 274 idxr, new_idx = convert_label_indexer(index, label, dim, method, tolerance) 275 pos_indexers[dim] = idxr 276 if new_idx is not None: ~/.conda/envs/xclim/lib/python3.8/site-packages/xarray/core/indexing.py in convert_label_indexer(index, label, index_name, method, tolerance) 119 ""cannot use ``method`` argument if any indexers are slice objects"" 120 ) --> 121 indexer = index.slice_indexer( 122 _sanitize_slice_element(label.start), 123 _sanitize_slice_element(label.stop), ~/.conda/envs/xclim/lib/python3.8/site-packages/pandas/core/indexes/base.py in slice_indexer(self, start, end, step, kind) 5684 slice(1, 3, None) 5685 """""" -> 5686 start_slice, end_slice = self.slice_locs(start, end, step=step) 5687 5688 # return a slice ~/.conda/envs/xclim/lib/python3.8/site-packages/pandas/core/indexes/base.py in slice_locs(self, start, end, step, kind) 5892 end_slice = None 5893 if end is not None: -> 5894 end_slice = self.get_slice_bound(end, ""right"") 5895 if end_slice is None: 5896 end_slice = len(self) ~/.conda/envs/xclim/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_slice_bound(self, label, side, kind) 5796 # For datetime indices label may be a string that has to be converted 5797 # to datetime boundary according to its resolution. -> 5798 label = self._maybe_cast_slice_bound(label, side) 5799 5800 # we need to look up the label TypeError: _maybe_cast_slice_bound() missing 1 required positional argument: 'kind' ``` **Anything else we need to know?**: A quick diagnostic suggests that `convert_label_indexer` should call pandas.Index.slice_indexer with a `kind` argument. **Environment**:
Output of xr.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 3.8.6 | packaged by conda-forge | (default, Jan 25 2021, 23:21:18) [GCC 9.3.0] python-bits: 64 OS: Linux OS-release: 5.4.0-77-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: ('en_CA', 'UTF-8') libhdf5: 1.10.6 libnetcdf: 4.7.4 xarray: 0.18.2 pandas: 1.3.0 numpy: 1.20.0 scipy: 1.6.3 netCDF4: 1.5.5.1 pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.4.1 nc_time_axis: 1.2.0 PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.3.2 dask: 2021.01.1 distributed: 2021.01.1 matplotlib: 3.4.2 cartopy: None seaborn: None numbagg: None pint: 0.16.1 setuptools: 49.6.0.post20210108 pip: 21.0.1 conda: None pytest: 6.2.2 IPython: 7.20.0 sphinx: 4.0.2
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5576/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 741100024,MDExOlB1bGxSZXF1ZXN0NTE5NDc0NzQz,4573,Update xESMF link to pangeo-xesmf in related-projects,81219,closed,0,,,1,2020-11-11T22:00:34Z,2020-11-12T14:54:08Z,2020-11-12T14:53:56Z,CONTRIBUTOR,,0,pydata/xarray/pulls/4573," The new link is where development now occurs. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4573/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 369639339,MDU6SXNzdWUzNjk2MzkzMzk=,2481,Implement CFPeriodIndex,81219,closed,0,,,3,2018-10-12T17:20:04Z,2020-11-02T01:26:48Z,2020-11-02T01:26:48Z,CONTRIBUTOR,,,,"A CFPeriodIndex supporting non-standard calendars would be useful to facilitate climate analyses. The use case for me would be to find the start and end date of a resampling group. This is useful to spot missing values in a resampled time series, or to create `time_bnds` arrays in a netCDF file. ``` import xarray as xr import pandas as pd cftime = xr.cftime_range(start='2000-01-01', periods=361, freq='D', calendar='360_day') pdtime = pd.date_range(start='2000-01-01', periods=361, freq='D') cf_da = xr.DataArray(range(361), coords={'time': cftime}, dims='time') pd_da = xr.DataArray(range(361), coords={'time': pdtime}, dims='time') #cf_c = cf_da.resample(time='M').count() pd_c = pd_da.resample(time='M').count() #cf_p = cf_c.indexes['time'].to_period() pd_p = pd_c.indexes['time'].to_period() #cf_expected_days_in_group = cf_p.end_time - cf_p.start_time + pd.offsets.Day(1) pd_expected_days_in_group = pd_p.end_time - pd_p.start_time + pd.offsets.Day(1) ``` Depends on #2191","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2481/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 492966281,MDU6SXNzdWU0OTI5NjYyODE=,3304,DataArray.quantile does not honor `keep_attrs`,81219,closed,0,,,3,2019-09-12T18:39:47Z,2020-04-05T18:56:30Z,2019-09-15T22:16:15Z,CONTRIBUTOR,,,,"#### MCVE Code Sample ```python # Your code here import xarray as xr da = xr.DataArray([0, 0], dims=""x"", attrs={'units':'K'}) out = da.quantile(.9, dim='x', keep_attrs=True) out.attrs ``` returns ``` OrderedDict() ``` #### Expected Output ``` OrderedDict([('units', 'K')]) ``` #### Output of ``xr.show_versions()``
# Paste the output here xr.show_versions() here INSTALLED VERSIONS ------------------ commit: 69c7e01e5167a3137c285cb50d1978252bb8bcbf python: 3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.15.0-60-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: en_CA.UTF-8 libhdf5: 1.10.2 libnetcdf: 4.6.1 xarray: 0.12.3+88.g69c7e01e.dirty pandas: 0.23.4 numpy: 1.16.1 scipy: 1.1.0 netCDF4: 1.3.1 pydap: installed h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.1 dask: 0.19.0 distributed: 1.23.0 matplotlib: 3.0.2 cartopy: 0.17.0 seaborn: None numbagg: None setuptools: 41.0.0 pip: 9.0.1 conda: None pytest: 4.4.0 IPython: 7.0.1 sphinx: 1.7.1
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3304/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 561210241,MDExOlB1bGxSZXF1ZXN0MzcyMDYyNTM2,3758,Fix interp bug when indexer shares coordinates with array,81219,closed,0,,,4,2020-02-06T19:06:22Z,2020-03-13T13:58:38Z,2020-03-13T13:58:38Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3758," - [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). ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3758/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 538620718,MDExOlB1bGxSZXF1ZXN0MzUzNzM1MDM4,3631,Add support for CFTimeIndex in get_clean_interp_index,81219,closed,0,,,11,2019-12-16T19:57:24Z,2020-01-26T18:36:24Z,2020-01-26T14:10:37Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3631," - [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 ? ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3631/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 539821504,MDExOlB1bGxSZXF1ZXN0MzU0NzMwNzI5,3642,Make datetime_to_numeric more robust to overflow errors,81219,closed,0,,,1,2019-12-18T17:34:41Z,2020-01-20T19:21:49Z,2020-01-20T19:21:49Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3642," - [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. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3642/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 492987154,MDExOlB1bGxSZXF1ZXN0MzE3MDU0MjUz,3305,Honor `keep_attrs` in DataArray.quantile,81219,closed,0,,,1,2019-09-12T19:27:14Z,2019-09-15T22:16:27Z,2019-09-15T22:16:15Z,CONTRIBUTOR,,0,pydata/xarray/pulls/3305," - [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. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3305/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull 455262061,MDU6SXNzdWU0NTUyNjIwNjE=,3018,Add quantile method to groupby object,81219,closed,0,,,4,2019-06-12T14:54:35Z,2019-07-02T16:23:57Z,2019-06-24T15:21:29Z,CONTRIBUTOR,,,,"Dataset and DataArray objects have a quantile method, but not GroupBy. This would be useful for climatological analyses. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3018/reactions"", ""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 461088361,MDU6SXNzdWU0NjEwODgzNjE=,3047,Assign attributes to DataArrays when creating dataset with PydapDataStore + subsetting,81219,closed,0,,,2,2019-06-26T17:14:10Z,2019-06-27T12:02:34Z,2019-06-27T12:02:33Z,CONTRIBUTOR,,,,"#### MCVE Code Sample ```python import xarray as xr # PyDAP access without subsetting - everything's fine url = 'http://remotetest.unidata.ucar.edu/thredds/dodsC/testdods/coads_climatology.nc' ds = xr.open_dataset(url, engine='pydap', decode_times=False) ds.TIME.units # yields 'hour since 0000-01-01 00:00:00' # PyDAP access with subsetting - variable attributes are global... dss = xr.open_dataset(url+'?SST[0:1:11][0:1:0][0:1:0]', engine='pydap', decode_times=False) print(dss.SST.attrs) # all good so far print(dss.TIME.attrs) # oh oh... nothing print(dss.attrs['TIME.units']) ``` #### Problem Description Opening a subsetted dataset with PydapDataStore creates global attributes instead of variable attributes. #### Expected Output All the global `TIME.*` attributes should be attributes of the `TIME` DataArray. #### Output of ``xr.show_versions()``
INSTALLED VERSIONS ------------------ commit: None python: 3.6.8 |Anaconda, Inc.| (default, Dec 30 2018, 01:22:34) [GCC 7.3.0] python-bits: 64 OS: Linux OS-release: 4.15.0-50-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: en_CA.UTF-8 libhdf5: 1.10.2 libnetcdf: 4.6.1 xarray: 0.12.1+60.g6fc855fb pandas: 0.23.4 numpy: 1.16.1 scipy: 1.1.0 netCDF4: 1.3.1 pydap: installed h5netcdf: None h5py: None Nio: None zarr: None cftime: 1.0.3.4 nc_time_axis: None PseudonetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.1 dask: 0.19.0 distributed: 1.23.0 matplotlib: 3.0.2 cartopy: 0.17.0 seaborn: None setuptools: 41.0.0 pip: 9.0.1 conda: None pytest: 4.4.0 IPython: 7.0.1 sphinx: 1.7.1
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3047/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue 423405197,MDExOlB1bGxSZXF1ZXN0MjYyOTgzOTcz,2828,Add quantile method to GroupBy,81219,closed,0,,,6,2019-03-20T18:20:41Z,2019-06-24T15:21:36Z,2019-06-24T15:21:29Z,CONTRIBUTOR,,0,pydata/xarray/pulls/2828," - [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. ","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2828/reactions"", ""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull