HTML exportieren

Es kann auch eine eigenständige HTML-Datei mit Bokeh-Inhalten generiert werden. Dies wird erreicht durch den Aufruf der Funktion output_file ("….html"):

from bokeh.io import output_notebook, show


output_notebook()

Loading BokehJS ...

import bokeh.sampledata


bokeh.sampledata.download()

Using data directory: /Users/veit/.bokeh/data
Skipping 'CGM.csv' (checksum match)
Skipping 'US_Counties.zip' (checksum match)
Skipping 'us_cities.json' (checksum match)
Skipping 'unemployment09.csv' (checksum match)
Skipping 'AAPL.csv' (checksum match)
Skipping 'FB.csv' (checksum match)
Skipping 'GOOG.csv' (checksum match)
Skipping 'IBM.csv' (checksum match)
Skipping 'MSFT.csv' (checksum match)
Skipping 'WPP2012_SA_DB03_POPULATION_QUINQUENNIAL.zip' (checksum match)
Skipping 'gapminder_fertility.csv' (checksum match)
Skipping 'gapminder_population.csv' (checksum match)
Skipping 'gapminder_life_expectancy.csv' (checksum match)
Skipping 'gapminder_regions.csv' (checksum match)
Skipping 'world_cities.zip' (checksum match)
Skipping 'airports.json' (checksum match)
Skipping 'movies.db.zip' (checksum match)
Skipping 'airports.csv' (checksum match)
Skipping 'routes.csv' (checksum match)
Skipping 'haarcascade_frontalface_default.xml' (checksum match)
Skipping 'SampleSuperstore.csv.zip' (checksum match)

import pandas as pd

from bokeh.plotting import figure
from bokeh.sampledata.stocks import AAPL


df = pd.DataFrame(AAPL)
df["date"] = pd.to_datetime(df["date"])

p = figure(width=800, height=250, x_axis_type="datetime")
p.line(df["date"], df["close"], color="navy", alpha=0.5)

GlyphRenderer(

id = 'p1092', …)

coordinates = None,

data_source = ColumnDataSource(id='p1086', ...),

glyph = Line(id='p1089', ...),

group = None,

hover_glyph = None,

js_event_callbacks = {},

js_property_callbacks = {},

level = 'glyph',

muted = False,

muted_glyph = Line(id='p1091', ...),

name = None,

nonselection_glyph = Line(id='p1090', ...),

propagate_hover = False,

selection_glyph = 'auto',

subscribed_events = PropertyValueSet(),

syncable = True,

tags = [],

view = CDSView(id='p1093', ...),

visible = True,

x_range_name = 'default',

y_range_name = 'default')

Schließlich konfigurieren wir mit output_file die Ausgabe von show():

from bokeh.io import output_file, show


output_file("plot.html")
show(p)