Categorical order in hierarchical axis not respected

ALL software version info

(this library, plus any other relevant software, e.g. bokeh, python, notebook, OS, browser, etc should be added within the dropdown below.)

Software Version Info

```plaintext Using Python 3.12.7 environment at /home/phil/.local/share/hatch/env/virtual/dask millions of cells/cMqPOBoB/dask millions of cells Package Version ------------------ ----------- asttokens 2.4.1 bleach 6.2.0 bokeh 3.6.1 certifi 2024.8.30 charset-normalizer 3.4.0 colorcet 3.1.0 comm 0.2.2 contourpy 1.3.1 cycler 0.12.1 debugpy 1.8.8 decorator 5.1.1 executing 2.1.0 fonttools 4.55.0 holoviews 1.20.0 idna 3.10 ipykernel 6.29.5 ipython 8.29.0 ipywidgets 8.1.5 jedi 0.19.2 jinja2 3.1.4 jupyter-client 8.6.3 jupyter-core 5.7.2 jupyterlab-widgets 3.0.13 kiwisolver 1.4.7 linkify-it-py 2.0.3 markdown 3.7 markdown-it-py 3.0.0 markupsafe 3.0.2 matplotlib 3.9.2 matplotlib-inline 0.1.7 mdit-py-plugins 0.4.2 mdurl 0.1.2 mizani 0.13.0 nest-asyncio 1.6.0 numpy 2.1.3 packaging 24.2 pandas 2.2.3 panel 1.5.4 param 2.1.1 parso 0.8.4 patsy 1.0.1 pexpect 4.9.0 pillow 11.0.0 platformdirs 4.3.6 plotnine 0.14.1 prompt-toolkit 3.0.48 psutil 6.1.0 ptyprocess 0.7.0 pure-eval 0.2.3 pygments 2.18.0 pyparsing 3.2.0 python-dateutil 2.9.0.post0 pytz 2024.2 pyviz-comms 3.0.3 pyyaml 6.0.2 pyzmq 26.2.0 requests 2.32.3 scipy 1.14.1 six 1.16.0 stack-data 0.6.3 statsmodels 0.14.4 tornado 6.4.1 tqdm 4.67.0 traitlets 5.14.3 typing-extensions 4.12.2 tzdata 2024.2 uc-micro-py 1.0.3 urllib3 2.2.3 wcwidth 0.2.13 webencodings 0.5.1 widgetsnbextension 4.0.13 xyzservices 2024.9.0 ```

Description of expected behavior and the observed behavior

When using multiple kvars, the category order is ignored:

Complete, minimal, self-contained example code that reproduces the issue

import pandas as pd
import holoviews as hv
hv.extension('bokeh')

cells_dtype = pd.CategoricalDtype(pd.array(["~1M", "~10M", "~100M"], dtype="string"), ordered=True)

df = pd.DataFrame(dict(
    cells=cells_dtype.categories.astype(cells_dtype),
    time=pd.array([2.99, 18.5, 835.2]),
    function=pd.array(["read", "read", "read"]),
))

hv.Bars(df, ["function", "cells"], ["time"])

Stack traceback and/or browser JavaScript console output

>>> df["cells"]
0      ~1M
1     ~10M
2    ~100M
Name: cells, dtype: category
Categories (3, string): [~1M < ~10M < ~100M]

Screenshots or screencasts of the bug in action

[x] I may be interested in making a pull request to address this

holoviz / holoviews