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

Representing graphs with Gephi

Gephi is an open source software for visualizing and analyzing large networks graphs which runs on Windows, Linux, and Mac OS X. We can freely download Gephi from its website listed as follows. For installation instructions please refer to the Appendix, Setting up the Infrastructure.

To visualize your social network graph, you just need to open Gephi, click on the File menu and select Open then we just need to look up and select our file myFacebookNet.gdf and click on the Open button. Then, we can see our graph as shown in the following screenshot:


For complete reference documentation about Gephi, please refer to the link

In the interface we can see the Context tab, which shows us the number of Nodes and Edges. We can show Node labels by clicking on the T icon in the bottom of the window. Finally, we can apply different layout algorithms by selecting in the ---Choose a layout dropdown in the Layout...