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Jupyter Cookbook

You're reading from   Jupyter Cookbook Over 75 recipes to perform interactive computing across Python, R, Scala, Spark, JavaScript, and more

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788839440
Length 238 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Table of Contents (12) Chapters Close

Preface 1. Installation and Setting up the Environment FREE CHAPTER 2. Adding an Engine 3. Accessing and Retrieving Data 4. Visualizing Your Analytics 5. Working with Widgets 6. Jupyter Dashboards 7. Sharing Your Code 8. Multiuser Jupyter 9. Interacting with Big Data 10. Jupyter Security 11. Jupyter Labs

Present a user-interactive graphic using Python


In this section, we use another Python library, bokeh, to display a chart where the user can adjust parameters of the graphic for different results.

Note

The installation instructions for the bokeh library are very complex. Again, they're specific to the operating system and version of Python you are using in your installation.

We are presenting online voter information, with the data points showing, for each user ID, how many votes they received for some post they made.

How to do it...

We can use this script:

from bokeh.io import output_notebook, show
from bokeh.layouts import widgetbox
from bokeh.models.widgets import TextInput
from bokeh.models import WidgetBox
import numpy as np
import pandas as pd
from bokeh.plotting import figure, show
from bokeh.layouts import layout

output_notebook()

# load the vote counts
from_counts = np.load("from_counts.npy")

# convert array to a dataframe (Histogram requires a dataframe)
df = pd.DataFrame({'Votes...
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