[DOC] Clear stale ImportError output from data_unequal notebook

[AnkitKumarIISERB]

Closes #3385

The rendered documentation page was showing a stale ImportError traceback
from a previous notebook execution with an incompatible sklearn version.
The underlying code in _continuous_interval_tree.py has since been updated
to use validate_data from a compatible sklearn version.

This PR clears the cached cell output so the docs page no longer renders
the error traceback.

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• Run pre-commit checks for all files
• Run mypy typecheck tests
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• Run all notebook example tests
• Run numba-disabled codecov tests
• Disable numba cache loading
• Regenerate expected results for testing
• Push an empty commit to re-run CI checks

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Pull request overview

This PR updates the data_unequal example notebook to remove stale, cached execution output (an ImportError traceback) that was rendering on the documentation site.

Changes:

• Cleared cached cell outputs and reset execution_count values in examples/datasets/data_unequal.ipynb.
• Reordered/normalized some per-cell metadata blocks.

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[TonyBagnall]

Thanks for looking at this. I don't think simply clearing the cached output fixes the issue though. Our docs use nbsphinx_execute = "never", so notebooks are not rerun during the documentation build

Could you rerun this notebook against the current aeon environment and commit the refreshed outputs instead? In particular, the all_estimators(...) cell should display the expected estimator list rather than have outputs: [].

It also looks like this change has cleared the outputs from all the other cells in the notebook, which we should retain.

[TonyBagnall]

see comment

[AnkitKumarIISERB]

Done! set up a Python 3.12 conda environment (numba crashes the kernel
on Python 3.13), reran the notebook, and committed the fresh outputs.
The all_estimators cell now shows the expected estimator list and all
5 code cells have fresh outputs. No ImportError or traceback remains.

Note: the failing CI check is examples/visualisation/plotting_estimators.ipynb
which is unrelated to this PR — data_unequal.ipynb passes in 7s.