Docs request (feature request?): Using ipympl when Jupyter and kernel are in different environments

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## Describe the issue

This issue is a continuation from https://github.com/matplotlib/ipympl/issues/112.

A very common use case involves a centrally-installed Jupyter instance running Jupyter kernels in various task-specific environments.

Examples include a shared Jupyterlab instance installed by a server administrator, or a single user with a highly-customized personal Jupyter configuration.

In these situations, it's usually undesirable (and sometimes impossible) for users to install and run Jupyter within their task-specific environment in order to make use of ipympl as per the official recommendation to use `pip install ipympl` for both the server/kernel-side package and the client/frontend-side extension.

What are the correct instructions for installing the "frontend" and "backend" components of ipympl separately, so that they can be used in two different environments?

If this is not currently a supported use case, consider this issue a much-desired feature request!

Inizia esaminando l’issue 112 di ipympl collegata e l’attuale raccomandazione ufficiale per l’installazione. Determina se gli ambienti Jupyter e kernel possono essere supportati separatamente, quindi documenta le istruzioni corrette per frontend/backend oppure indica chiaramente che questo caso d’uso non è supportato.

Scritto dal modello di indicizzazione a partire dal testo della issue.