What happened?

I was trying to do a scatterplot of my data with one dimension determining the color. The dimension has only a few values so I used hue_style="discrete" to have a different color for each value. However, the resulting scatterplot has a continuous colorbar, which is the same as when I pass hue_style="continuous":

What did you expect to happen?

The colorbar should have discrete colors. I was also expecting the colors to be from the default matplotlib color palette, C0, C1, etc, when there's less than 10 items, like this:

Although the examples in the documentation show the discrete case also using viridis.

What I was really expecting is a plot like one would get by passing add_colorbar=False, add_legend=True:

But that may be a bit too automagical.

Minimal Complete Verifiable Example

```Python import matplotlib.pyplot as plt import numpy as np import xarray as xr

x = xr.DataArray( np.random.default_rng().random((10, 3)), coords=[ ("idx", np.linspace(0, 1, 10)), ("color", [1, 2, 3]), ] ) y = x + np.random.default_rng().random(x.shape)

ds = xr.Dataset({ "x": x, "y": y, })

the output is the same regardless of hue_style="discrete" or "continuous" or just leaving it out

ds.plot.scatter(x="x", y="y", hue="color", hue_style="discrete", ax=plt.figure().gca()) ```

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, 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?

This is the code for the "expected" plot: ```python from matplotlib.colors import ListedColormap

ds.plot.scatter( x="x", y="y", hue="color", hue_style="discrete", ax=plt.figure().gca(),

# these lines added in addition to the MVCE
cmap=ListedColormap(["C0", "C1", "C2"]),
vmin=0.5, vmax=3.5,
cbar_kwargs=dict(ticks=ds.color.data),

) ```

Environment

INSTALLED VERSIONS ------------------ commit: None python: 3.8.10 (default, May 26 2023, 14:05:08) [GCC 9.4.0] python-bits: 64 OS: Linux OS-release: 5.14.0-1059-oem machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: ('en_US', 'UTF-8') libhdf5: None libnetcdf: None xarray: 2023.1.0 pandas: 1.4.3 numpy: 1.23.0 scipy: None netCDF4: None pydap: None h5netcdf: None h5py: None Nio: None zarr: None cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.5.3 cartopy: None seaborn: None numbagg: None fsspec: None cupy: None pint: None sparse: None flox: None numpy_groupies: None setuptools: 44.0.0 pip: 20.0.2 conda: None pytest: None mypy: None IPython: 8.12.2 sphinx: None

I also tried this on main at 3459e6fa, the behavior is the same.