該特定示例結合了HoloView和散景組件以及散景小部件都無法在筆記本中輕鬆與Python進行通信。但是,您可以使用holoviews的「洗刷器」小工具來實現同樣的功能:
import pandas as pd
import numpy as np
import holoviews as hv
from bokeh.sampledata import gapminder
hv.extension('bokeh')
# Switch to sending data 'live' and using the scrubber widget
%output widgets='live' holomap='scrubber'
# Declare dataset
panel = pd.Panel({'Fertility': gapminder.fertility,
'Population': gapminder.population,
'Life expectancy': gapminder.life_expectancy})
gapminder_df = panel.to_frame().reset_index().rename(columns={'minor': 'Year'})
gapminder_df = gapminder_df.merge(gapminder.regions.reset_index(), on='Country')
gapminder_df['Country'] = gapminder_df['Country'].astype('str')
gapminder_df['Group'] = gapminder_df['Group'].astype('str')
gapminder_df.Year = gapminder_df.Year.astype('f')
ds = hv.Dataset(gapminder_df)
# Apply dimension labels and ranges
kdims = ['Fertility', 'Life expectancy']
vdims = ['Country', 'Population', 'Group']
dimensions = {
'Fertility' : dict(label='Children per woman (total fertility)', range=(0, 10)),
'Life expectancy': dict(label='Life expectancy at birth (years)', range=(15, 100)),
'Population': ('population', 'Population')
}
# Create Points plotting fertility vs life expectancy indexed by Year
gapminder_ds = ds.redim(**dimensions).to(hv.Points, kdims, vdims, 'Year')
# Define annotations
text = gapminder_ds.clone({yr: hv.Text(1.2, 25, str(int(yr)), fontsize=30)
for yr in gapminder_ds.keys()})
# Define options
opts = {'plot': dict(width=1000, height=600,tools=['hover'], size_index='Population',
color_index='Group', size_fn=np.sqrt, title_format="{label}"),
'style': dict(cmap='Set1', size=0.3, line_color='black', alpha=0.6)}
text_opts = {'style': dict(text_font_size='52pt', text_color='lightgray')}
# Combine Points and Text
(gapminder_ds({'Points': opts}) * text({'Text': text_opts})).relabel('Gapminder Demo')