What are the main differences between visualizing data in the notebook and on a dashboard?
The main differences are as follows:
- The audience for the dashboard is meant to be wide—so the dashboard should be easily accessible, for example, via an internet browser, and well-explained. One-off visualizations, on the other hand, are often made for self-consumption, and thus don't need to be self-explanatory.
- Dashboards are meant to be frequently updated and exploratory. Visualizations are often static and show a specific aspect of data.
Why do we call some dashboards "static"? What are the pros and cons of a static dashboard?
In common terms, static web pages are ones that are provided "as-is," as flat files, and there is no active server behind them. Static dashboards are easier to maintain and provide for a wide audience but have some limitations in terms of computation and data access.
What are the benefits of using a dynamic dashboard?
Dynamic dashboards are actively served by dedicated servers and thus have considerable computation power behind them. The servers can also have access to the "raw" data and compute metrics on the fly, allowing for much deeper exploration possibilities.
What are the features of the panel package?
panel is a package that was developed by Anaconda (the same company that produces the Conda package manager). Its main feature is that it is agnostic to actual visualization tools—any tool can be used if it produces content that can be present in the Jupyter Notebook.