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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
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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 2. Adding an Engine FREE CHAPTER 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 line graph using Python


We will use a basic plot() to show how graphics work in Python to generate a line graph. Then, we will use several other libraries for other interesting visualizations available from Python.

For this example, we are using made-up data to determine the number of births that have the same name and producing a line plot of the data.

How to do it...

We can use this Python script:

import pandas
import matplotlib
%matplotlib inline

baby_name = ['Alice','Charles','Diane','Edward']
number_births = [96, 155, 66, 272]
dataset = list(zip(baby_name,number_births))
df = pandas.DataFrame(data = dataset, columns=['Name', 'Number'])
df['Number'].plot()

With the resulting plot as:

This is fictitious data, but it does show a good, clean graphic.

How it works...

pandas is the built-in Python library for dealing with a dataset. matplotlib is the Python library that will plot our data. We use the command %matplotlib inline to have the plot show up in our notebook. Otherwise, Python...

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