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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 Mac OS X


The easiest way to get matplotlib on Mac OS X is to use prepackaged python distributions such as Enthought Python Distribution (EPD). Just go to the EPD site and download and install the latest stable version for your OS.

In case you are not satisfied with EPD or cannot use it for other reasons such as versions distributed with it, there is a manual (read: harder) way of installing Python, matplotlib, and its dependencies.

Getting ready

We will use the Homebrew project that eases installation of all software that Apple did not install on your OS, including Python and matplotlib. Under the hood, Homebrew is a set of Ruby and Git that automate download and installation. Following these instructions should get the installation working. First, we will install Homebrew, and then Python, followed by tools such as virtualenv, then dependencies for matplotlib (NumPy and SciPy), and finally matplotlib. Hold on, here we go.

How to do it...

  1. In your Terminal paste and execute the following command:

    ruby <(curl -fsSkL raw.github.com/mxcl/homebrew/go)
    

    After the command finishes, try running brew update or brew doctor to verify that installation is working properly.

  2. Next, add the Homebrew directory to your system path, so the packages you install using Homebrew have greater priority than other versions. Open ~/.bash_profile (or /Users/[your-user-name]/.bash_profile) and add the following line to the end of file:

    export PATH=/usr/local/bin:$PATH
    
  3. You will need to restart the terminal so it picks a new path. Installing Python is as easy as firing up another one-liner:

    brew install python --framework --universal
    

    This will also install any prerequisites required by Python.

  4. Now, you need to update your path (add to the same line):

    export PATH=/usr/local/share/python:/usr/local/bin:$PATH
    
  5. To verify that installation worked, type python --version at the command line, you should see 2.7.3 as the version number in the response.

  6. You should have pip installed by now. In case it is not installed, use easy_install to add pip:

    $ easy_install pip
    
  7. Now, it's easy to install any required package; for example, virtualenv and virtualenvwrapper are useful:

    pip install virtualenv
    pip install virtualenvwrapper
    
  8. Next step is what we really wanted to do all along—install matplotlib:

    pip install numpy
    brew install gfortran
    pip install scipy
    

    Note

    Mountain Lion users will need to install the development version of SciPy (0.11) by executing the following line:

    pip install -e git+https://github.com/scipy/scipy#egg=scipy-dev
    
  9. Verify that everything is working. Call Python and execute the following commands:

    import numpy
    print numpy.__version__
    import scipy
    print scipy.__version__
    quit()
    
  10. Install matplotlib:

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