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Mastering Python Data Visualization

You're reading from   Mastering Python Data Visualization Generate effective results in a variety of visually appealing charts using the plotting packages in Python

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Product type Paperback
Published in Oct 2015
Publisher
ISBN-13 9781783988327
Length 372 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (11) Chapters Close

Preface 1. A Conceptual Framework for Data Visualization 2. Data Analysis and Visualization FREE CHAPTER 3. Getting Started with the Python IDE 4. Numerical Computing and Interactive Plotting 5. Financial and Statistical Models 6. Statistical and Machine Learning 7. Bioinformatics, Genetics, and Network Models 8. Advanced Visualization A. Go Forth and Explore Visualization Index

Summary

There is a good set of tools and packages for Python developers that are available today. Python has a large standard library. This is commonly cited as one of Python's greatest strengths. It has modules to create the graphical user interfaces, connecting to relational databases, pseudorandom number generators, arithmetic with arbitrary precision decimals, manipulating regular expressions. In addition, there are high-performance packages to plot 2D and 3D graphics, machine learning and statistical algorithms, and so on.

We have seen that the IDE tools (such as Canopy and Anaconda) have leveraged the efficient development work from a computation and visualization standpoint, among many other areas. There are many effective ways to produce visualization methods using these tools. In the following few chapters, interesting examples will be shown with these tools and packages.

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