Book Image

Practical Data Analysis

By : Hector Cuesta
Book Image

Practical Data Analysis

By: Hector Cuesta

Overview of this book

Plenty of small businesses face big amounts of data but lack the internal skills to support quantitative analysis. Understanding how to harness the power of data analysis using the latest open source technology can lead them to providing better customer service, the visualization of customer needs, or even the ability to obtain fresh insights about the performance of previous products. Practical Data Analysis is a book ideal for home and small business users who want to slice and dice the data they have on hand with minimum hassle.Practical Data Analysis is a hands-on guide to understanding the nature of your data and turn it into insight. It will introduce you to the use of machine learning techniques, social networks analytics, and econometrics to help your clients get insights about the pool of data they have at hand. Performing data preparation and processing over several kinds of data such as text, images, graphs, documents, and time series will also be covered.Practical Data Analysis presents a detailed exploration of the current work in data analysis through self-contained projects. First you will explore the basics of data preparation and transformation through OpenRefine. Then you will get started with exploratory data analysis using the D3js visualization framework. You will also be introduced to some of the machine learning techniques such as, classification, regression, and clusterization through practical projects such as spam classification, predicting gold prices, and finding clusters in your Facebook friends' network. You will learn how to solve problems in text classification, simulation, time series forecast, social media, and MapReduce through detailed projects. Finally you will work with large amounts of Twitter data using MapReduce to perform a sentiment analysis implemented in Python and MongoDB. Practical Data Analysis contains a combination of carefully selected algorithms and data scrubbing that enables you to turn your data into insight.
Table of Contents (24 chapters)
Practical Data Analysis
About the Author
About the Reviewers

Installing and running Python 3

Python is a general-purpose programming language whose design philosophy emphasizes batteries included, which provides clear and logical programs on small and large scale.

The latest versions of Ubuntu and Fedora come with Python 2.7 out of the box. In this book, we will use Python 3.2 for the code examples and projects. Python comes with a large set of standard libraries that support many common programming tasks such as collections, connecting to web servers, high-performance scientific computing, searching text with regular expressions, reading and modifying files.

We will make use of several Python libraries such as numpy, scipy, mlpy, nose, pymongo. In this chapter, we will see how to install and set up all these libraries. We can find more information on the Python's official website,

Installing and running Python 3.2 on Ubuntu

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

$ sudo apt-get install python3

To check whether everything is installed correctly, just execute the following command:

$ python3

Installing and running IDLE on Ubuntu

To install IDLE, just open a command prompt and run the following command:

$ sudo apt-get install idle3

To check whether everything is installed correctly, just execute the following command:

$ idle3

Installing and running Python 3.2 on Windows

First, download Python 3.2 from the official website,

The Windows version is provided as an MSI package. To install it manually, just double click the /python-3.2.3.msi file:

By design, Python installs to a directory with the version number embedded. In this case, Python version is 3.2 and will install at C:\Python32\, so that you can have multiple versions of Python on the same system without any conflicts.


Python does not automatically modify the PATH environment variable, so you will need to do it manually. Right-click on My Computer, select Properties, Advance System Settings, and click on the Environment Variables button.

Now edit the PATH system-variable and add ;C:\Python32\;C:\Python32\Scripts\ to its end.

To check whether everything is installed correctly, just execute the following command in the Windows terminal:

>> python

Installing and running IDLE on Windows

IDLE is already installed with Python MSI installation, to run it just navigate to Start | All Programs | Python 3.2 | IDLE (Python GUI):


The easy_install command makes it easy to fetch and install Python libraries and their dependencies. The most crucial third-party Python software of all is Distribute , which extends the packaging and installation facilities provided by distutils in the standard library.

To obtain the latest version of Distribute for Windows, run the Python script available at Download and execute distribute-0.6.35.win32-py3.2.exe. Now easy_install gets installed into c:\Python32\Scripts.