- bamboolib (proprietary license - acquired by Databricks in order to run within the Databricks notebooks)
- mito (GPL license)
- dtale (MIT license)
One benefit of having them in actual code is that you can programmatically automate the creation of things like dashboards and reports. For instance, schedule a script to share an interactive plot every Monday morning, or build a live dashboard that updates every 10m. This opens up a lot of possibilities that would be impossible in a traditional drag-and-drop tool.
I am one of the co-founders of bamboolib and we are actively thinking about adding support for altair to the Plot Creator (instead of just relying on Plotly).
Since we are talking other viz options in Python, there are of course also matplotlib, seaborn, plotly, and more.
That's an awesome use case for Python, and that sort of script generation is one of the main reasons that we see people adopting Python/Mito. And specifically, graphing[1] is one of the most popular features in Mito.
Mito generates Plotly [2] graphs, and of course generates the Plotly graph code too, so you can customize the graphs to your perfect liking (Plotly has great documentation and a lot of customizations) or schedule the script to run automatically.
[1] https://docs.trymito.io/how-to/graphing [2] https://plotly.com/