Viewing

hvPlot is written to work well inside a Jupyter notebook, from the interactive Python command prompt, or inside a Python batch script. In this user guide we will discover how to use hvPlot to view plots in each of these cases and how to save the plots to a separate file.

Notebook

In a Jupyter notebook, hvPlot will return HoloViews objects that display themselves using Bokeh. First, we'll import a supported data-library backend, in this case the convenient intake data catalog:

In [1]:
import intake
import hvplot
import hvplot.intake