In case you didn’t catch it, above @DanieleDamaris I suggested running %pip install seaborn in the notebook. This has the advantage that it should install the package to the same environment backing the notebook without the user needing to sort out which version is backing the environment being used by the notebook. It’s a useful practice for Jupyter work, and also works for conda installs, see here for more information.
But you are right, since that didn’t seem to fix the situation, it wouldn’t hurt in this case to try installing the way you suggest.
The magic route should work most times on up to date systems and installs, and since it makes things so much easier for new learners I wanted to highlight it further in this thread.
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