hvPlot 0.10 has just been released! Checkout the blog post and support hvPlot by giving it a 🌟 on Github.


import hvplot.pandas  # noqa

scatter plots are a good first way to plot data with non continuous axes.

from bokeh.sampledata.iris import flowers as df

sepal_length sepal_width petal_length petal_width species
149 5.9 3.0 5.1 1.8 virginica
125 7.2 3.2 6.0 1.8 virginica
0 5.1 3.5 1.4 0.2 setosa
55 5.7 2.8 4.5 1.3 versicolor
141 6.9 3.1 5.1 2.3 virginica
df.hvplot.scatter(x='sepal_length', y='sepal_width', by='species', 
                  legend='top', height=400, width=400)

As for most other types of hvPlot plots, you can add fields to the hover display using the hover_cols argument. It can also take “all” as input to show all fields.

df.hvplot.scatter(x='sepal_length', y='sepal_width', s='petal_length', scale=5, by='species', 
                  legend='top', height=400, width=600,
                  hover_cols=["species", "sepal_length", "sepal_width", "petal_width"])

You can add the ‘s’ parameter in scatter to specify the marker plot size and add the ‘scale’ parameter to specify what the scaling factor should be.