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Python Data Visualization Cookbook

You're reading from   Python Data Visualization Cookbook As a developer with knowledge of Python you are already in a great position to start using data visualization. This superb cookbook shows you how in plain language and practical recipes, culminating with 3D animations.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Length 280 pages
Edition 1st Edition
Languages
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Author (1):
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Igor Milovanovic Igor Milovanovic
Author Profile Icon Igor Milovanovic
Igor Milovanovic
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Table of Contents (15) Chapters Close

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment FREE CHAPTER 2. Knowing Your Data 3. Drawing Your First Plots and Customizing Them 4. More Plots and Customizations 5. Making 3D Visualizations 6. Plotting Charts with Images and Maps 7. Using Right Plots to Understand Data 8. More on matplotlib Gems Index

Creating a stem plot


A two-dimensional stem plot displays data as lines extending from a baseline along the x axis. A circle (the default) or other marker, whose y axis represents the data value, terminates each stem.

In this recipe we will be discussing how to create a stem plot.

Do not confuse stem with stem and leaf plots, which is a method of representing data by separating the last important digit of values as leaves and higher order values as stems.

Getting ready

For this kind of plot we want to use a sequence of discrete data, where ordinary line plots will not make sense anyway.

Plot discrete sequences as stems, where data values are represented as markers at the end of each stem. Stems extend from the baseline (usually at y = 0) to the data point value.

How to do it...

We will use matplotlib to plot stem plots using the stem() function. This function can use just a series of y values when x values are generated as a simple sequence from 0 to len(y) - 1. If we provide the stem() function...

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