Updated `See also` section in the docstrings broke numpydoc

What happened?

Hi, I would like to report that https://github.com/pydata/xarray/pull/8311 broke the documentation build of Datashader. Datashader's documentation uses Sphinx and numpydoc to process its docstrings. It turns out (I had no idea) that numpydoc processes more doctrings than I'd have expected, including xarray's ones. The changes in the PR made numpydoc unhappy. To reproduce run:

python3 -m venv .venv                                                                                         
source .venv/bin/activate
pip install numpydoc
python -m numpydoc.hooks.validate_docstrings xarray/core/dataarray.py

You'll get this error:

ValueError: Error parsing See Also entry ':doc:`xarray-tutorial:intermediate/indexing/indexing`'

I'm pretty sure this is not an xarray issue but felt that opening an issue here might be useful for others encountering this issue. Really, feel free to close it.

What did you expect to happen?

No response

Minimal Complete Verifiable Example

No response

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.
• Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

No response

Anything else we need to know?

No response

Environment

Start by running python -m numpydoc.hooks.validate_docstrings xarray/core/dataarray.py in the reported virtual environment and inspect the See Also changes from pull request 8311. Determine whether the xarray docstrings should be adjusted to avoid the numpydoc parsing error; done means validation no longer reports the cited error or the issue is shown to belong to numpydoc instead.