The closest Python equivalent to RStudio is the JupyterLab Desktop app[1,2], which I highly recommend. I've entirely switched to using it for teaching, and it

The closest Python equivalent to RStudio is the JupyterLab Desktop app[1,2], which I highly recommend. I've entirely switched to using it for teaching, and it is a godsend, since it works the same way across platforms (win/mac/linux), installs its own Python interpreter independent of any system Python the student might have, and even comes with NumPy/SciPy/Pandas/Seaborn/statsmodels already installed, which makes it possible for me to skip the `pip ...` or `conda ...` instructions altogether. Between the standalone desktop app, and the convenience of running JypyterLab in the cloud thanks to https://mybinder.org/ https://mybinder.org/ links, there is now a smooth path for beginners getting into stats/ML/data science: (1) read notebook on github or nbviewer, (2) run notebooks in the cloud via mybinder links, (3) install JupyterLab Desktop app, (4) learn to install Python+env-manager via command line. Previously, new learners were forced to jump straight to (4), but now there are logical steps along the way! [1] https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-ov-file#jupyterlab-desktop https://github.com/jupyterlab/jupyterlab-desktop?tab=readme-... [2] https://blog.jupyter.org/jupyterlab-desktop-app-now-available-b8b661b17e9a https://blog.jupyter.org/jupyterlab-desktop-app-now-availabl...