Doc: Include Jupyter Lab directive to render

[duanasq]

I am using Jupyter Lab 3.0.1. I followed the instructions here using plotly 5.13.0 but I was getting a blank white output. as below. Adding the directive mentioned made it render.

Documentation PR

• I've 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 master 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 in new/modified examples
• 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 / plotly.io as pio
• Data frames are always called df
• fig = <something> call is 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=...) in every new/modified example
• Specific adders and updaters like fig.add_shape and fig.update_xaxes are used instead of big fig.update_layout calls in every new/modified example
• fig.show() is at the end of each new/modified example
• plotly.plot() and plotly.iplot() are not used in any new/modified example
• Hex codes for colors are not used in any new/modified example in favour of these nice ones