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

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!

首先检查链接的 ipympl issue 112 以及当前官方安装建议。确定是否可以分别支持 Jupyter 和 kernel 环境，然后记录正确的 frontend/backend 操作说明，或者明确说明不支持此用例。