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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

Building NumPy, SciPy, matplotlib, and IPython from source

As a last resort or if we want to have the latest code, we can build from source. In practice, it shouldn't be that hard, although depending on your operating system, you might run into problems. As operating systems and related software are rapidly evolving, in such cases, the best you can do is search online or ask for help. In this chapter, we give pointers on good places to look for help.

The source code can be retrieved with git or as an archive from GitHub. The steps to install NumPy from source are straightforward and given here. We can retrieve the source code for NumPy with git as follows:

$ git clone git://github.com/numpy/numpy.git numpy

Note

There are similar commands for SciPy, matplotlib, and IPython (refer to the table that follows after this piece of information). The IPython source code can be downloaded from https://github.com/ipython/ipython/releases as a source archive or ZIP file. You can then unpack it with your favorite tool or with the following command:

$ tar -xzf ipython.tar.gz

Please refer to the following table for the git commands and source archive/zip links:

Library

Git command

Tarball/zip URL

NumPy

git clone git://github.com/numpy/numpy.git numpy

https://github.com/numpy/numpy/releases

SciPy

git clone http://github.com/scipy/scipy.git scipy

https://github.com/scipy/scipy/releases

matplotlib

git clone git://github.com/matplotlib/matplotlib.git

https://github.com/matplotlib/matplotlib/releases

IPython

git clone --recursive https://github.com/ipython/ipython.git

https://github.com/ipython/ipython/releases

Install on /usr/local with the following command from the source code directory:

$ python setup.py build
$ sudo python setup.py install --prefix=/usr/local

To build, we need a C compiler such as GCC and the Python header files in the python-dev or python-devel package.

You have been reading a chapter from
Python Data Analysis
Published in: Oct 2014
Publisher:
ISBN-13: 9781783553358
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