JupyterLite cannot really see your system files due to the browser sandboxing it runs in. (In fact, one of the big things being focused on is making it possible to interact better with local storage.) Therefore, it cannot use your libraries installed locally at this time. (Not to mention, they wouldn't be compiled on your system to use webassembly and thus incompatible.)
A lot of the modules in the Python data science stack has already been converted to WebAssembly support.
You can see example of how to install several of these exploring the example notebooks in the pyolite
directory available from here.
You use piplite
which is a wrapper around micropip
. (piplite
being a wrapper is stated here](https://jupyterlite.readthedocs.io/en/latest/quickstart/using.html).)
Here's how it is suggested to install several at this time:
import piplite
await piplite.install('numpy')
await piplite.install('pandas')
await piplite.install('matplotlib')
await piplite.install('bokeh')
This is a rapidly developing ecosystem, and so it helps to keep following the updates in a thread at the Jupyter Discourse Forum. Following Jeremy Tuloup on Twitter is highly recommended as well.
Usage tip
Note that I refer to a current site offering JupyterLite here. If you fear you may have already accessed this page and edited some and lost track which are the official versions of the notebooks vs. those you edited, a nice trick is to access the site in an incognito window on your computer. Those windows won't be linked to your browser cache for that site and so you get a 'clean' version of what is currently available from the location.