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Practical Data Analysis

You're reading from   Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Length 360 pages
Edition 1st Edition
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Author (1):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
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Table of Contents (24) Chapters Close

Practical Data Analysis
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started FREE CHAPTER 2. Working with Data 3. Data Visualization 4. Text Classification 5. Similarity-based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Disease with Cellular Automata 10. Working with Social Graphs 11. Sentiment Analysis of Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with IPython and Wakari Setting Up the Infrastructure Index

Installing and running SciPy


According to the official website http://www.scipy.org/, SciPy (pronounced as Sigh Pie) is an open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, and powerful enough to be used by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer, and display or publish the results, give SciPy a try!

Installing and running SciPy on Ubuntu

To install SciPy, simply open a command prompt and run the following command:

$ sudo apt-get install python3-scipy

To check whether everything is installed correctly, just execute the Python Shell as follows:

$ idle3

Then execute the following commands:

>>> import scipy
>>> scipy.test()

Installing and running SciPy on Windows

First, download the SciPy 0.12 from the official website, http://sourceforge.net/projects/scipy/files/scipy/0.12.0b1/.

The Windows version is provided as an .exe package. To install it manually, just double click the /scipy-0.12.0b1-win32-superpack-python3.2.exe/ file.

To check whether everything is installed correctly, just navigate to Start | All Programs | Python 3.2 | IDLE (Python GUI).

Then execute the following commands:

>>> import scipy
>>> scipy.test()
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