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Practical Data Analysis

You're reading from  Practical Data Analysis

Product type Book
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Pages 360 pages
Edition 1st Edition
Languages
Author (1):
Hector Cuesta Hector Cuesta
Profile icon Hector Cuesta
Toc

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 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

Importance of data visualization


The goal of the data visualization is to expose something new about the underlying patterns and relationships contained within the data. The visualization not only needs to look good but also meaningful in order to help organizations make better decisions. Visualization is an easy way to jump into a complex dataset (small or big) to describe and explore the data efficiently.

Many kinds of data visualizations are available such as bar chart, histogram, line chart, pie chart, heat maps, frequency Wordle (as shown in the following figure) and so on, for one variable, two variables, and many variables in one, two, or three dimensions.

Data visualization is an important part of our data analysis process because it is a fast and easy way to do an exploratory data analysis through summarizing their main characteristics with a visual graph.

The goals of exploratory data analysis are listed as follows:

  • Detection of data errors

  • Checking of assumptions

  • Finding hidden patterns (such as tendency)

  • Preliminary selection of appropriate models

  • Determining relationships between the variables

We will get into more detail about data visualization and exploratory data analysis in Chapter 3, Data Visualization.

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Practical Data Analysis
Published in: Oct 2013 Publisher: Packt ISBN-13: 9781783280995
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