9 stories
Nine probe notebooks, three export paths, twenty-seven conversion attempts, and a count of what actually survives into each PDF. The LaTeX route keeps every column of a wide DataFrame and drops four of eight Unicode strings; the browser routes do the reverse, and clip a long source line as well.
The package imports in your terminal and fails in the notebook. Four virtual environments, nine notebook runs, and the one line of jupyter_client source that decides which Python your kernel actually runs — with the audit script that answers it for your machine.
The common nbconvert PDF export errors, each with real terminal output, the actual cause, and a fix. Covers PandocMissing, xelatex not found, missing .sty files, webpdf/Playwright, and kernel errors.
Learn how to use Jupyter nbconvert to export .ipynb notebooks to HTML, PDF, Python scripts, Markdown, and slides. Includes commands and examples for every output format.
What Jupyter's .ipynb_checkpoints folders are, whether it is safe to delete them, and why adding them to .gitignore does not untrack the ones you already committed - with a throwaway repository showing exactly what each untracking command does to your index.
Install Jupyter Notebook on Mac with a venv, Conda, Homebrew, or JupyterLab Desktop — including the real "externally-managed-environment" error a global pip install hits on Homebrew Python, and the versions a clean venv install gets today.
Python is quick and easy to code, but can be slow when doing intensive numerical operations. Translating code to Cython can be helpful, but in most cases requires a bit of trial and error to achieve the optimal result.
In software, it's said that all abstractions are leaky, and this is true for the Jupyter notebook as it is for any other software. I most often see this manifest itself with the following issue: I installed package X and now I can't import it in the notebook. Help!
Jupyter notebooks provide a useful environment for interactive exploration of data. A common question I get, though, is how you can progress from this nonlinear, interactive, trial-and-error style of exploration to a more linear and reproducible analysis based on organized, packaged, and tested…
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