Bokeh Tutorial — Sharing and Embedding



In [1]:

    
import pandas as pd
from bokeh.plotting import figure

AAPL = pd.read_csv(
    "http://ichart.yahoo.com/table.csv?s=AAPL&a=0&b=1&c=2000&d=0&e=1&f=2015",
    parse_dates=['Date'])
MSFT = pd.read_csv(
    "http://ichart.yahoo.com/table.csv?s=MSFT&a=0&b=1&c=2000&d=0&e=1&f=2015",
    parse_dates=['Date'])
IBM = pd.read_csv(
    "http://ichart.yahoo.com/table.csv?s=IBM&a=0&b=1&c=2000&d=0&e=1&f=2015",
    parse_dates=['Date'])

def make_figure():
    p = figure(x_axis_type="datetime", width=700, height=300)

    p.line(AAPL['Date'], AAPL['Adj Close'], color='#A6CEE3', legend='AAPL')
    p.line(IBM['Date'], IBM['Adj Close'], color='#33A02C', legend='IBM')
    p.line(MSFT['Date'], MSFT['Adj Close'], color='#FB9A99', legend='MSFT')

    p.title = "Stock Closing Prices"
    p.grid.grid_line_alpha=0.3
    p.xaxis.axis_label = 'Date'
    p.yaxis.axis_label = 'Price'
    p.legend.orientation = "top_left"
    return p

Embed functions all look for a Plot object. Common plot objects are:

Plot from models
figure from plotting
Chart from charts
vplot, hplot from plotting

Displaying in the Notebook



In [2]:

    
from bokeh.io import output_notebook, show



In [3]:

    
output_notebook()









    




    
        
        
        
    
        
        BokehJS successfully loaded.



In [4]:

    
p = make_figure()
show(p)

Saving to an HTML File



In [5]:

    
from bokeh.io import output_file, show



In [6]:

    
output_file("tutorial_sharing.html")



In [7]:

    
p = make_figure()
show(p)   # save(p) will save without opening a new browser tab

Publishing to a Bokeh Server

Templating in HTML Documents



In [6]:

    
import jinja2
from bokeh.embed import components



In [7]:

    
template = jinja2.Template("""
<!DOCTYPE html>
<html lang="en-US">

<link
    href="http://cdn.pydata.org/bokeh/release/bokeh-0.9.0.min.css"
    rel="stylesheet" type="text/css"
>
<script 
    src="http://cdn.pydata.org/bokeh/release/bokeh-0.9.0.min.js"
></script>

<body>

    <h1>Hello Bokeh!</h1>
    
    <p> Below is a simple plot of stock closing prices </p>
    
    {{ script }}
    
    {{ div }}

</body>

</html>
""")



In [9]:

    
p = make_figure()
script, div = components(p)



In [10]:

    
from IPython.display import HTML
HTML(template.render(script=script, div=div))









    Out[10]:














    Hello Bokeh!
    
     Below is a simple plot of stock closing prices



In [12]:

    
from flask import Flask
app = Flask(__name__)

@app.route('/')
def hello_bokeh():
    return template.render(script=script, div=div)



In [13]:

    
# Uncomment to run the Flask Server. Use Kernel -> Interrupt from Notebook menubar to stop 
#app.run(port=5050)



In [14]:

    
# EXERCISE: Create your own template (or modify the one above)



In [ ]:

Bokeh Tutorial — Sharing and Embedding

Creating a Plot to Share

Displaying in the Notebook

Saving to an HTML File

Publishing to a Bokeh Server

Templating in HTML Documents

Hello Bokeh!