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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
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Author (1):
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Kirthi Raman Kirthi Raman
Author Profile Icon Kirthi Raman
Kirthi Raman
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Table of Contents (16) Chapters Close

Mastering Python Data Visualization
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. A Conceptual Framework for Data Visualization FREE CHAPTER 2. Data Analysis and Visualization 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 Go Forth and Explore Visualization Index

Packages installed with Anaconda


The following command will display a list of all the packages in the Anaconda environment:

conda list 

The featured packages in Anaconda are Astropy, Cython, h5py, IPython, LLVM, LLVMpy, matplotlib, Mayavi, NetworkX, NLTK, Numexpr, Numba, numpy, pandas, Pytables, scikit-image, scikit-learn, scipy, Spyder, Qt/PySide, and VTK.

In order to check the packages that are installed with Anaconda, navigate to the command line and enter the conda list command to quickly display a list of all the packages installed in the default environment. Alternatively, you can also check Continuum Analytics for details on the list of packages available in the current and latest release.

In addition, you can always install a package with the usual means, for example, using the pip install command or from the source using a setup.py file. Although conda is the preferred packaging tool, there is nothing special about Anaconda that prevents the usage of standard Python packaging tools.

Note

IPython is not required, but it is highly recommended. IPython should be installed after Python, GNU Readline, and PyReadline are installed. Anaconda and Canopy does these things by default. There are Python packages that are used in all the examples in this book for a good reason. In the following section, we have updated the list.

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