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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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Toc

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

Generating a histogram using Python


In this example, we generate a histogram of random numbers. In this case, we are simulating rolling dice 1,000 times and recording the resultant face value.

How to do it...

We can use this Python script:

import pylab
import random

random.seed(113)

samples = 1000
dice = []
for i in range(samples):
 total = random.randint(1,6) + random.randint(1,6)
 dice.append(total)

pylab.hist(dice, bins= pylab.arange(1.5,12.6,1.0))
pylab.show()

This results in a histogram display:

This is the graph showing almost exactly what we expected. I imagine that with a higher cycle count, we would have got closer to a pure pyramid peaking at 7.

How it works...

For the histogram, we use the pylab library. We also use the random library to simulate the dice rolls.

We first set the random seed to a fixed value. This allows you to reproduce the results I have shown exactly.

Next, we simulate rolling the dice 1,000 times and record the results in an array. In this case, we are just recording...

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