Add Plotly.js docs updates for 6.3

[LiamConnors]

Adds examples for next Plotly.js version

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Documentation PR

• I have seen the doc/README.md file.
• This change runs in the current version of Plotly on PyPI and targets the doc-prod branch OR it targets the main branch.
• If this PR modifies the first example in a page or adds a new one, it is a px example if at all possible.
• Every new/modified example has a descriptive title and motivating sentence or paragraph.
• Every new/modified example is independently runnable.
• Every new/modified example is optimized for short line count and focuses on the Plotly/visualization-related aspects of the example rather than the computation required to produce the data being visualized.
• Meaningful/relatable datasets are used for all new examples instead of randomly-generated data where possible.
• The random seed is set if using randomly-generated data.
• New/modified remote datasets are loaded from https://plotly.github.io/datasets and added to https://github.com/plotly/datasets.
• Large computations are avoided in the new/modified examples in favour of loading remote datasets that represent the output of such computations.
• Imports are plotly.graph_objects as go, plotly.express as px, and/or plotly.io as pio.
• Data frames are always called df.
• fig = <something> is called high up in each new/modified example (either px.<something> or make_subplots or go.Figure).
• Liberal use is made of fig.add_* and fig.update_* rather than go.Figure(data=..., layout=...).
• Specific adders and updaters like fig.add_shape and fig.update_xaxes are used instead of big fig.update_layout calls.
• fig.show() is at the end of each example.
• plotly.plot() and plotly.iplot() are not used in any example.
• Named colors are used instead of hex codes wherever possible.
• Code blocks are marked with ```python.

[cceneag]

This pull request updates the documentation for Plotly's Python library to include new features introduced in version 6.3, along with some minor metadata updates. The key changes introduce examples for controlling zero line layers, limiting legend height, and using custom SVG patterns in bar charts.

New Features in Documentation:

Axes:

• Added an example for controlling the zero line layer using the zerolinelayer property, allowing users to display zero lines above or below traces.

Legends:

• Introduced a new section on setting the maximum height of legends with the maxheight parameter, allowing better layout control when legends have many items.

Patterns:

• Added an example demonstrating the use of custom SVG paths for bar chart patterns via the marker.pattern.path property, enabling highly customizable visualizations.

Metadata Updates:

• Updated jupytext_version to 1.17.2 across all modified files. [1] [2] [3]
• Downgraded Python version metadata from 3.10.x to 3.9.0 for consistency across documentation files. [1] [2] [3]