We're happy to offer embedded Jupyter notebooks as part of the One Codex platform – facilitating both large-scale analyses (diversity estimation, visualization, machine learning, etc.) and a nice environment for rapid development against our API. See our blog post announcing notebooks or take a look at a basic tutorial notebook or more advanced example that uses the One Codex Python client library and v1 API.
If you're familiar with Python (or R), you'll find that these notebooks give you the ability to do almost anything with the results on One Codex. In addition to making figures and performing sophisticated statistical analyses you can share these notebooks with collaborators, providing a reproducible framework for communicating scientific research.
Note that if you're logged in you can also click copy this notebook to copy these tutorials into your own account and then run and modify them from there.