Box#
Download this notebook from GitHub (right-click to download).
import hvplot.pandas # noqa
box plots are most useful when grouped by additional dimensions.
from bokeh.sampledata.sprint import sprint as df
df.head()
| Name | Country | Medal | Time | Year | |
|---|---|---|---|---|---|
| 0 | Usain Bolt | JAM | GOLD | 9.63 | 2012 |
| 1 | Yohan Blake | JAM | SILVER | 9.75 | 2012 |
| 2 | Justin Gatlin | USA | BRONZE | 9.79 | 2012 |
| 3 | Usain Bolt | JAM | GOLD | 9.69 | 2008 |
| 4 | Richard Thompson | TRI | SILVER | 9.89 | 2008 |
boxplot = df.hvplot.box(y='Time', by='Medal', height=400, width=400, legend=False)
boxplot
Overlay this plot with the jittered scatter plot of the medalist times using the * operator:
boxplot * df.hvplot.scatter(y='Time', x='Medal', c='orange').opts(jitter=0.5)
Use groupby to create a separate plot for each medal type with a widget for selecting between the plots.
df.hvplot.box(y='Time', groupby='Medal', by='Country', ylabel='Sprint Time', height=400, width=600)
This web page was generated from a Jupyter notebook and not all interactivity will work on this website. Right click to download and run locally for full Python-backed interactivity.
Download this notebook from GitHub (right-click to download).