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Python Data Visualization Cookbook (Second Edition)

You're reading from   Python Data Visualization Cookbook (Second Edition) Visualize data using Python's most popular libraries

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781784396695
Length 302 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

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 the Right Plots to Understand Data 8. More on matplotlib Gems 9. Visualizations on the Clouds with Plot.ly Index

Conventions

In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "We packed our little demo in the DemoPIL class, so that we can extend it easily, while sharing the common code around the demo function, run_fixed_filters_demo."

A block of code is set as follows:

def my_function(x):
    return x*x

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

for a in range(10):
    print a

Any command-line input or output is written as follows:

$ sudo python setup.py install

Note

Warnings or important notes appear in a box like this.

Tip

Tips and tricks appear like this.

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