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Python Data Visualization Cookbook

You're reading from  Python Data Visualization Cookbook

Product type Book
Published in Nov 2013
Publisher Packt
ISBN-13 9781782163367
Pages 280 pages
Edition 1st Edition
Languages
Author (1):
Igor Milovanovic Igor Milovanovic
Profile icon Igor Milovanovic

Table of Contents (15) Chapters

Python Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Preparing Your Working Environment 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

Installing matplotlib on Windows


In this recipe, we will demonstrate how to install Python and start working with matplotlib installation. We assume Python was not previously installed.

Getting ready

There are two ways of installing matplotlib on Windows. The easier way is by installing prepackaged Python environments such as EPD, Anaconda and Python(x,y). This is the suggested way to install Python, especially for beginners.

The second way is to install everything using binaries of precompiled matplotlib and required dependencies. This is more difficult as you have to be careful about the versions of NumPy and SciPy you are installing, as not every version is compatible with the latest version of matplotlib binaries. The advantage in this is that you can even compile your particular versions of matplotlib or any library as to have the latest features, even if they are not provided by authors.

How to do it...

The suggested way of installing free or commercial Python scientific distributions is as easy as following the steps provided on the project's website.

If you just want to start using matplotlib and don't want to be bothered with Python versions and dependencies, you may want to consider using the Enthought Python Distribution (EPD). EPD contains prepackaged libraries required to work with matplotlib and all the required dependencies (SciPy, NumPy, IPython, and more).

As usual, we download Windows Installer (*.exe) that will install all the code we need to start using matplotlib and all recipes from this book.

There is also a free scientific project Python(x,y) (http://code.google.com/p/pythonxy/) for Windows 32-bit system that contains all dependencies resolved, and is an easy (and free!) way of installing matplotlib on Windows. Because Python(x,y) is compatible with Python modules installers, it can be easily extended with other Python libraries. No Python installation should be present on the system before installing Python(x,y).

Let me shortly explain how we would install matplotlib using precompiled Python, NumPy, SciPy, and matplotlib binaries. First, we download and install standard Python using official MSI Installer for our platform (x86 or x86-64). After that, download official binaries for NumPy and SciPy and install them first. When you are sure that NumPy and SciPy are properly installed, then we download the latest stable release binary for matplotlib and install it by following the official instructions.

There's more...

Note that many examples are not included in the Windows installer. If you want to try the demos, download the matplotlib source and look in the examples subdirectory.

You have been reading a chapter from
Python Data Visualization Cookbook
Published in: Nov 2013 Publisher: Packt ISBN-13: 9781782163367
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