This example demonstrates the use of bokeh in the sphinx-nbgallery.
The example is taken from the bokeh-notebook gallery to demonstrate the use
bokeh. For the sphinx-nbgallery, you have to do 3 additional modifications
in the example_gallery_config
of your conf.py
:
insert_bokeh
configuration value because we need
additional style sheets and javascript filesoutput_notebook
function needs some time, werecommend to use the dont_preprocess
configuration value for this
notebook.
3. We cannot estimate a thumbnail figure for a notebook not using matplotlib.
So you should provide it using the thumbnail_figure
metadata key (as it
has been done for this notebook)
from bokeh.models import HoverTool, ColumnDataSource
from bokeh.palettes import Viridis6
from bokeh.plotting import figure, show, output_notebook
from bokeh.sampledata.us_counties import data as counties
from bokeh.sampledata.unemployment import data as unemployment
counties = {
code: county for code, county in counties.items() if county["state"] == "tx"
}
county_xs = [county["lons"] for county in counties.values()]
county_ys = [county["lats"] for county in counties.values()]
county_names = [county['name'] for county in counties.values()]
county_rates = [unemployment[county_id] for county_id in counties]
county_colors = [Viridis6[int(rate/3)] for rate in county_rates]
source = ColumnDataSource(data=dict(
x=county_xs,
y=county_ys,
color=county_colors,
name=county_names,
rate=county_rates,
))
TOOLS="pan,wheel_zoom,box_zoom,reset,hover,save"
p = figure(title="Texas Unemployment 2009", tools=TOOLS,
x_axis_location=None, y_axis_location=None)
p.grid.grid_line_color = None
p.patches('x', 'y', source=source,
fill_color='color', fill_alpha=0.7,
line_color="white", line_width=0.5)
hover = p.select_one(HoverTool)
hover.point_policy = "follow_mouse"
hover.tooltips = [
("Name", "@name"),
("Unemployment rate)", "@rate%"),
("(Long, Lat)", "($x, $y)"),
]
show(p)
<Bokeh Notebook handle for In[6]>