html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/4641#issuecomment-749323873,https://api.github.com/repos/pydata/xarray/issues/4641,749323873,MDEyOklzc3VlQ29tbWVudDc0OTMyMzg3Mw==,15331990,2020-12-22T03:55:33Z,2020-12-22T03:55:33Z,CONTRIBUTOR,"Maybe a simple fix would be to replace `np.unique` with `pd.unique` since it's ordered?
```
Hash table-based unique. Uniques are returned in order of appearance. This does NOT sort.
Significantly faster than numpy.unique. Includes NA values.
```
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.unique.html","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,755105132
https://github.com/pydata/xarray/issues/4641#issuecomment-749250751,https://api.github.com/repos/pydata/xarray/issues/4641,749250751,MDEyOklzc3VlQ29tbWVudDc0OTI1MDc1MQ==,14808389,2020-12-21T23:22:11Z,2020-12-21T23:22:11Z,MEMBER,"this is caused by the use of `np.unique` here: https://github.com/pydata/xarray/blob/de3f27553fd480e247a3f1f7d377fec0f5f2759c/xarray/plot/dataset_plot.py#L425
to fix that, I think we either need to find a way to preserve the order of `data[""hue""]` (the output of `np.unique` is sorted), or we have to use `sorted`/`np.unique` here: https://github.com/pydata/xarray/blob/de3f27553fd480e247a3f1f7d377fec0f5f2759c/xarray/plot/facetgrid.py#L384","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,755105132
https://github.com/pydata/xarray/issues/4641#issuecomment-746969091,https://api.github.com/repos/pydata/xarray/issues/4641,746969091,MDEyOklzc3VlQ29tbWVudDc0Njk2OTA5MQ==,1217238,2020-12-16T20:33:08Z,2020-12-16T20:33:08Z,MEMBER,"Ugh, this is unfortunate! Thanks for the clear example code. Coincidentally, one of collaborators ran into this same bug this morning. This sort of ""corrupted data"" bug is one of the nastiest types, so we should definitely try to prioritize a fix.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,755105132
https://github.com/pydata/xarray/issues/4641#issuecomment-737853069,https://api.github.com/repos/pydata/xarray/issues/4641,737853069,MDEyOklzc3VlQ29tbWVudDczNzg1MzA2OQ==,42246615,2020-12-03T10:31:33Z,2020-12-03T10:42:32Z,NONE,"Here are the plots demonstrating what I mean.
The “upright” rectangle (in the intervals [0, 0.5] and [0, 2]) of points represents the data corresponding to category ""A"". However, it is colored in blue, which corresponds to category ""B"". The order of labels in the legend is correct in the sense that it conserves the order in the Dataset.
In the second image, the color assignment in the plot is correct – data corresponding to category ""A"" is still colored in blue but that now corresponds to category ""A"". The legend is now alphabetically ordered instead of conserving the order the category coordinate in the Dataset.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,755105132
https://github.com/pydata/xarray/issues/4641#issuecomment-737617144,https://api.github.com/repos/pydata/xarray/issues/4641,737617144,MDEyOklzc3VlQ29tbWVudDczNzYxNzE0NA==,1217238,2020-12-03T02:18:20Z,2020-12-03T02:18:20Z,MEMBER,"could you share an image showing what the incorrect plot(s) looks like? you should be able to ""paste"" into the comment field in GitHub","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,755105132
https://github.com/pydata/xarray/issues/4641#issuecomment-737190620,https://api.github.com/repos/pydata/xarray/issues/4641,737190620,MDEyOklzc3VlQ29tbWVudDczNzE5MDYyMA==,42246615,2020-12-02T12:09:48Z,2020-12-02T12:09:48Z,NONE,"As my original plot still was wrong after updating I investigated a bit further: The problem persists when also faceting.
Here is my new example where, again, data of category ""A"" get colored as ""B"" and vice versa.
```python
import xarray as xr
import numpy as np
u = np.random.rand(50, 2, 2) * np.array([1, 2])
v = np.random.rand(50, 2) * np.array([1, 0.5])
ds = xr.Dataset(
{
""u"": ((""x"", ""foo"", ""category""), u),
""v"": ((""x"", ""category""), v),
},
coords={""category"": [""B"", ""A""], ""foo"": [1, 2]}
)
g = ds.plot.scatter(
y=""u"",
x=""v"",
hue=""category"",
col=""foo""
);
```
I am sorry for the confusion.
Output of `xr.show_versions()`
INSTALLED VERSIONS
------------------
commit: None
python: 3.7.8 | packaged by conda-forge | (default, Nov 27 2020, 19:24:58)
[GCC 9.3.0]
python-bits: 64
OS: Linux
OS-release: 4.15.0-122-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.16.2
pandas: 1.1.2
numpy: 1.17.5
scipy: 1.5.3
netCDF4: 1.5.4
pydap: None
h5netcdf: None
h5py: 2.10.0
Nio: None
zarr: 2.4.0
cftime: 1.3.0
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.26.0
distributed: 2.30.1
matplotlib: 3.3.2
cartopy: None
seaborn: 0.11.0
numbagg: None
pint: None
setuptools: 49.6.0.post20201009
pip: 20.3
conda: 4.8.3
pytest: 6.0.1
IPython: 7.19.0
sphinx: None